{
  "aboutHtml": "<p>Nemotron 3.5 ASR Streaming Multilingual 0.6B ialah model pengecaman pertuturan NVIDIA dengan 600 juta parameter untuk transkripsi langsung dan beban kerja audio rakaman. Model ini memperluas barisan penstriman bahasa Inggeris dengan penyesuaian berdasarkan ID bahasa. Pertuturan menjadi teks dalam bahasa input, dengan tanda baca dan huruf besar terbina dalam output.</p><p>Liputan bahasa pengeluar mempunyai tiga peringkat. Sembilan belas lokal sedia transkripsi meliputi bahasa Inggeris AS dan UK, Sepanyol AS dan Sepanyol, Perancis di Perancis dan Kanada, Itali, Portugis Brazil dan Portugal, Belanda, Jerman, Turki, Rusia, Arab, Hindi, Jepun, Korea, Vietnam dan Ukraine. Tiga belas lokal liputan luas menambah bahasa Poland, Sweden, Czech, Bokmål Norway, Denmark, Bulgaria, Finland, Croatia, Slovak, Mandarin, Hungary, Romania dan Estonia. Bersama-sama, 32 lokal ini menghasilkan transkripsi tanpa penalaan halus tambahan.</p><p>Lapan lokal sedia penyesuaian—bahasa Yunani, Lithuania, Latvia, Malta, Slovenia, Ibrani, Thai dan Nynorsk Norway—dikenali oleh tokenizer tetapi memerlukan penalaan halus dalam domain untuk mendayakan transkripsi penuh. Oleh itu, angka 40 lokal pengeluar bukan dakwaan bahawa kesemua empat puluh mempunyai keupayaan sedia guna yang sama. Checkpoint tersuai ialah artifak yang berasingan daripada model asas.</p><p>Seni bina menggabungkan pengekod FastConformer 24 lapisan yang sedar cache dengan penyahkod RNN-T. Model ini mengekalkan keadaan perhatian dan konvolusi pengekod daripada bingkai terdahulu serta memproses setiap ketul audio baharu tanpa berulang kali mengira semula tetingkap bertindih. Isyarat ID bahasa dibekalkan bersama perwakilan akustik untuk menyesuaikan transkrip berdasarkan bahasa atau membiarkan model menyimpulkan bahasa.</p><p>Konfigurasi NeMo NVIDIA mendokumenkan saiz ketul 80, 160, 320, 560 dan 1120 milisaat. Tetapan perhatian mengawal jumlah audio masa hadapan yang diterima ketul sebelum teks dikeluarkan, membolehkan tugas mengimbangkan masa menunggu dan konteks akustik. Ini ialah konfigurasi penstriman pengeluar, bukannya masa respons hujung ke hujung yang dijamin; pelaksanaan boleh mendedahkan subset sokongannya sendiri.</p><p>Sediakan audio WAV mono pada kadar sampel 16 kHz pemproses pengeluar. Apabila bahasa diketahui, gunakan penyesuaian berdasarkan lokal yang sepadan; mod automatik mengesan bahasa yang dituturkan. Contoh saluran asas menggunakan prom bahasa Inggeris AS secara lalai, maka tingkah laku berbilang bahasa perlu dikonfigurasi dengan sengaja dan bukannya diandaikan daripada contoh itu.</p><p>Dalam mod automatik, aliran kerja pengeluar boleh menambah tag bahasa selepas tanda baca penamat transkrip. Mengekalkan tag itu menyediakan bahasa kepada aplikasi yang mengendalikan trafik berbilang bahasa; membuangnya mengembalikan teks transkrip yang bersih. Kekalkan perbezaan antara perkataan yang dikenal pasti, tanda bacanya dan metadata bahasa ini apabila memaparkan atau memproses hasil.</p><p>Aplikasi kapsyen boleh membekalkan audio mengikut turutan, mengumpulkan transkrip dan menggunakan teks yang lengkap untuk paparan atau pemprosesan hiliran. Aplikasi suara boleh menghantar pertuturan yang dikenal pasti kepada peringkat pemahaman bahasanya. Kerja analisis panggilan boleh menyimpan rakaman asal dan transkrip bersama-sama supaya nama, nombor dan istilah tidak biasa kekal boleh disemak. Model ASR membekalkan transkrip; peringkasan, tindakan dan penjanaan pertuturan ialah peringkat aplikasi yang berasingan.</p><p>NVIDIA melatih model pada campuran data pertuturan awam dan proprietari dengan label manusia serta sintetik yang dinormalkan kepada teks bertanda baca dan penggunaan huruf besar yang betul. Panduan penyesuaiannya menekankan pemadanan label bahasa dan gaya teks, kemudian penilaian audio yang diketepikan daripada latihan pada tetapan penstriman yang dimaksudkan untuk penggunaan. Ia menerangkan penyesuaian bahasa, loghat dan domain tanpa menjadikan hasil tersuai itu sifat checkpoint asal.</p><p>Kad model mengaitkan panjang rakaman praktikal dengan memori yang tersedia dan bukannya menerbitkan satu had tempoh sejagat. Bezakan edisi berbilang bahasa daripada model bahasa Inggeris sahaja, dan simpan bahasa terpilih serta konfigurasi penstriman bersama hasil transkripsi. Artifak output ialah teks yang dikenal pasti, dengan metadata bahasa pengeluar secara pilihan, dan bukannya jawapan perbualan umum.</p>",
  "aboutText": "Nemotron 3.5 ASR Streaming Multilingual 0.6B ialah model pengecaman pertuturan NVIDIA dengan 600 juta parameter untuk transkripsi langsung dan beban kerja audio rakaman. Model ini memperluas barisan penstriman bahasa Inggeris dengan penyesuaian berdasarkan ID bahasa. Pertuturan menjadi teks dalam bahasa input, dengan tanda baca dan huruf besar terbina dalam output.\n\nLiputan bahasa pengeluar mempunyai tiga peringkat. Sembilan belas lokal sedia transkripsi meliputi bahasa Inggeris AS dan UK, Sepanyol AS dan Sepanyol, Perancis di Perancis dan Kanada, Itali, Portugis Brazil dan Portugal, Belanda, Jerman, Turki, Rusia, Arab, Hindi, Jepun, Korea, Vietnam dan Ukraine. Tiga belas lokal liputan luas menambah bahasa Poland, Sweden, Czech, Bokmål Norway, Denmark, Bulgaria, Finland, Croatia, Slovak, Mandarin, Hungary, Romania dan Estonia. Bersama-sama, 32 lokal ini menghasilkan transkripsi tanpa penalaan halus tambahan.\n\nLapan lokal sedia penyesuaian—bahasa Yunani, Lithuania, Latvia, Malta, Slovenia, Ibrani, Thai dan Nynorsk Norway—dikenali oleh tokenizer tetapi memerlukan penalaan halus dalam domain untuk mendayakan transkripsi penuh. Oleh itu, angka 40 lokal pengeluar bukan dakwaan bahawa kesemua empat puluh mempunyai keupayaan sedia guna yang sama. Checkpoint tersuai ialah artifak yang berasingan daripada model asas.\n\nSeni bina menggabungkan pengekod FastConformer 24 lapisan yang sedar cache dengan penyahkod RNN-T. Model ini mengekalkan keadaan perhatian dan konvolusi pengekod daripada bingkai terdahulu serta memproses setiap ketul audio baharu tanpa berulang kali mengira semula tetingkap bertindih. Isyarat ID bahasa dibekalkan bersama perwakilan akustik untuk menyesuaikan transkrip berdasarkan bahasa atau membiarkan model menyimpulkan bahasa.\n\nKonfigurasi NeMo NVIDIA mendokumenkan saiz ketul 80, 160, 320, 560 dan 1120 milisaat. Tetapan perhatian mengawal jumlah audio masa hadapan yang diterima ketul sebelum teks dikeluarkan, membolehkan tugas mengimbangkan masa menunggu dan konteks akustik. Ini ialah konfigurasi penstriman pengeluar, bukannya masa respons hujung ke hujung yang dijamin; pelaksanaan boleh mendedahkan subset sokongannya sendiri.\n\nSediakan audio WAV mono pada kadar sampel 16 kHz pemproses pengeluar. Apabila bahasa diketahui, gunakan penyesuaian berdasarkan lokal yang sepadan; mod automatik mengesan bahasa yang dituturkan. Contoh saluran asas menggunakan prom bahasa Inggeris AS secara lalai, maka tingkah laku berbilang bahasa perlu dikonfigurasi dengan sengaja dan bukannya diandaikan daripada contoh itu.\n\nDalam mod automatik, aliran kerja pengeluar boleh menambah tag bahasa selepas tanda baca penamat transkrip. Mengekalkan tag itu menyediakan bahasa kepada aplikasi yang mengendalikan trafik berbilang bahasa; membuangnya mengembalikan teks transkrip yang bersih. Kekalkan perbezaan antara perkataan yang dikenal pasti, tanda bacanya dan metadata bahasa ini apabila memaparkan atau memproses hasil.\n\nAplikasi kapsyen boleh membekalkan audio mengikut turutan, mengumpulkan transkrip dan menggunakan teks yang lengkap untuk paparan atau pemprosesan hiliran. Aplikasi suara boleh menghantar pertuturan yang dikenal pasti kepada peringkat pemahaman bahasanya. Kerja analisis panggilan boleh menyimpan rakaman asal dan transkrip bersama-sama supaya nama, nombor dan istilah tidak biasa kekal boleh disemak. Model ASR membekalkan transkrip; peringkasan, tindakan dan penjanaan pertuturan ialah peringkat aplikasi yang berasingan.\n\nNVIDIA melatih model pada campuran data pertuturan awam dan proprietari dengan label manusia serta sintetik yang dinormalkan kepada teks bertanda baca dan penggunaan huruf besar yang betul. Panduan penyesuaiannya menekankan pemadanan label bahasa dan gaya teks, kemudian penilaian audio yang diketepikan daripada latihan pada tetapan penstriman yang dimaksudkan untuk penggunaan. Ia menerangkan penyesuaian bahasa, loghat dan domain tanpa menjadikan hasil tersuai itu sifat checkpoint asal.\n\nKad model mengaitkan panjang rakaman praktikal dengan memori yang tersedia dan bukannya menerbitkan satu had tempoh sejagat. Bezakan edisi berbilang bahasa daripada model bahasa Inggeris sahaja, dan simpan bahasa terpilih serta konfigurasi penstriman bersama hasil transkripsi. Artifak output ialah teks yang dikenal pasti, dengan metadata bahasa pengeluar secara pilihan, dan bukannya jawapan perbualan umum.",
  "editorialOverlay": {
    "copy_fields": null,
    "copy_sha256": null,
    "copy_source": null,
    "html_sha256": "ba04834af9901650fc34800f07ff21edb6685594b3e37bcf91c44ffe83a12f16",
    "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06",
    "raw_model_unchanged": true,
    "schema": "ailoot-native-model-editorial-v1"
  },
  "locale": "ms",
  "methods": [
    {
      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">NV</span><h2 id=\"sheet-title\">NVIDIA: Nemotron 3.5 ASR Streaming Multilingual 0.6B</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>NVIDIA /</span><code>nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b</code><button type=\"button\" id=\"copy-id\">Salin ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Bahagian kad model\"><button type=\"button\" data-card-jump=\"overview\">Pengenalan</button><button type=\"button\" data-card-jump=\"methods\">Input &amp; kaedah</button><button type=\"button\" data-card-jump=\"pricing\">Pelan harga</button><button type=\"button\" data-card-jump=\"examples\">Contoh</button><button type=\"button\" data-card-jump=\"results\">Hasil</button><button type=\"button\" data-card-jump=\"aliases\">Alias</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Kaedah API\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|transcriptions|/v1/audio/transcriptions|nvidia%2Fnemotron-3.5-asr-streaming-multilingual-0.6b\">Pengecaman</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-0\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">Pengenalan</h3><p class=\"mdesc-full\">Nemotron 3.5 ASR Streaming Multilingual 0.6B NVIDIA mentranskripsikan pertuturan menjadi teks bertanda baca menggunakan pengekod penstriman yang sedar cache. Model ini menyokong penyesuaian berdasarkan bahasa secara jelas atau pengesanan automatik, dengan 32 lokal sedia untuk transkripsi dan lapan memerlukan penyesuaian.</p><dl class=\"card-io\" data-card-io><div><dt>Input yang diterima</dt><dd>Audio</dd></div><div><dt>Hasil</dt><dd>Teks</dd></div></dl><details class=\"card-about\"><summary>Tentang model</summary><p class=\"note-s\" data-model-method-boundary>Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>Nemotron 3.5 ASR Streaming Multilingual 0.6B ialah model pengecaman pertuturan NVIDIA dengan 600 juta parameter untuk transkripsi langsung dan beban kerja audio rakaman. Model ini memperluas barisan penstriman bahasa Inggeris dengan penyesuaian berdasarkan ID bahasa. Pertuturan menjadi teks dalam bahasa input, dengan tanda baca dan huruf besar terbina dalam output.</p><p>Liputan bahasa pengeluar mempunyai tiga peringkat. Sembilan belas lokal sedia transkripsi meliputi bahasa Inggeris AS dan UK, Sepanyol AS dan Sepanyol, Perancis di Perancis dan Kanada, Itali, Portugis Brazil dan Portugal, Belanda, Jerman, Turki, Rusia, Arab, Hindi, Jepun, Korea, Vietnam dan Ukraine. Tiga belas lokal liputan luas menambah bahasa Poland, Sweden, Czech, Bokmål Norway, Denmark, Bulgaria, Finland, Croatia, Slovak, Mandarin, Hungary, Romania dan Estonia. Bersama-sama, 32 lokal ini menghasilkan transkripsi tanpa penalaan halus tambahan.</p><p>Lapan lokal sedia penyesuaian—bahasa Yunani, Lithuania, Latvia, Malta, Slovenia, Ibrani, Thai dan Nynorsk Norway—dikenali oleh tokenizer tetapi memerlukan penalaan halus dalam domain untuk mendayakan transkripsi penuh. Oleh itu, angka 40 lokal pengeluar bukan dakwaan bahawa kesemua empat puluh mempunyai keupayaan sedia guna yang sama. Checkpoint tersuai ialah artifak yang berasingan daripada model asas.</p><p>Seni bina menggabungkan pengekod FastConformer 24 lapisan yang sedar cache dengan penyahkod RNN-T. Model ini mengekalkan keadaan perhatian dan konvolusi pengekod daripada bingkai terdahulu serta memproses setiap ketul audio baharu tanpa berulang kali mengira semula tetingkap bertindih. Isyarat ID bahasa dibekalkan bersama perwakilan akustik untuk menyesuaikan transkrip berdasarkan bahasa atau membiarkan model menyimpulkan bahasa.</p><p>Konfigurasi NeMo NVIDIA mendokumenkan saiz ketul 80, 160, 320, 560 dan 1120 milisaat. Tetapan perhatian mengawal jumlah audio masa hadapan yang diterima ketul sebelum teks dikeluarkan, membolehkan tugas mengimbangkan masa menunggu dan konteks akustik. Ini ialah konfigurasi penstriman pengeluar, bukannya masa respons hujung ke hujung yang dijamin; pelaksanaan boleh mendedahkan subset sokongannya sendiri.</p><p>Sediakan audio WAV mono pada kadar sampel 16 kHz pemproses pengeluar. Apabila bahasa diketahui, gunakan penyesuaian berdasarkan lokal yang sepadan; mod automatik mengesan bahasa yang dituturkan. Contoh saluran asas menggunakan prom bahasa Inggeris AS secara lalai, maka tingkah laku berbilang bahasa perlu dikonfigurasi dengan sengaja dan bukannya diandaikan daripada contoh itu.</p><p>Dalam mod automatik, aliran kerja pengeluar boleh menambah tag bahasa selepas tanda baca penamat transkrip. Mengekalkan tag itu menyediakan bahasa kepada aplikasi yang mengendalikan trafik berbilang bahasa; membuangnya mengembalikan teks transkrip yang bersih. Kekalkan perbezaan antara perkataan yang dikenal pasti, tanda bacanya dan metadata bahasa ini apabila memaparkan atau memproses hasil.</p><p>Aplikasi kapsyen boleh membekalkan audio mengikut turutan, mengumpulkan transkrip dan menggunakan teks yang lengkap untuk paparan atau pemprosesan hiliran. Aplikasi suara boleh menghantar pertuturan yang dikenal pasti kepada peringkat pemahaman bahasanya. Kerja analisis panggilan boleh menyimpan rakaman asal dan transkrip bersama-sama supaya nama, nombor dan istilah tidak biasa kekal boleh disemak. Model ASR membekalkan transkrip; peringkasan, tindakan dan penjanaan pertuturan ialah peringkat aplikasi yang berasingan.</p><p>NVIDIA melatih model pada campuran data pertuturan awam dan proprietari dengan label manusia serta sintetik yang dinormalkan kepada teks bertanda baca dan penggunaan huruf besar yang betul. Panduan penyesuaiannya menekankan pemadanan label bahasa dan gaya teks, kemudian penilaian audio yang diketepikan daripada latihan pada tetapan penstriman yang dimaksudkan untuk penggunaan. Ia menerangkan penyesuaian bahasa, loghat dan domain tanpa menjadikan hasil tersuai itu sifat checkpoint asal.</p><p>Kad model mengaitkan panjang rakaman praktikal dengan memori yang tersedia dan bukannya menerbitkan satu had tempoh sejagat. Bezakan edisi berbilang bahasa daripada model bahasa Inggeris sahaja, dan simpan bahasa terpilih serta konfigurasi penstriman bersama hasil transkripsi. Artifak output ialah teks yang dikenal pasti, dengan metadata bahasa pengeluar secara pilihan, dan bukannya jawapan perbualan umum.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Tersedia di Ailoot · input &amp; kaedah</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Transkripsi</b> <code>POST /v1/audio/transcriptions</code></summary><dl class=\"method-capabilities\"><div><dt>Input</dt><dd><code>audio</code></dd></div><div><dt>Output</dt><dd><code>text</code></dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Medan</th><th>Jenis</th><th>Keperluan</th><th>Nilai &amp; had</th><th>Lalai</th></tr></thead><tbody><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">input_audio</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">language</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">temperature</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Minimum: 0</div><div>Maksimum: 1</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">response_format</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>json, verbose_json</div></td><td data-cell-label=\"Lalai\" data-default=\"known\"><span class=\"card-cell-label\">Lalai</span>json</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">timestamp_granularities</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>array</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">provider</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Parameter kaedah dan kitar hayat</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Kontrak</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>model, input_audio</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>audio</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_conditions</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>Baca fail WAV sebenar dan kodkan bait sebenarnya untuk input_audio JSON yang diisytiharkan; tiada laluan multipart ditawarkan bagi pengisytiharan tepat yang hanya menggunakan JSON ini.</td></tr></tbody></table></div><p>Kitar hayat: <code>synchronous_result_then_owned_library</code></p><p class=\"note-s\"><code>GET /v1/media/tasks/{task_id}</code> · task_id sebenar yang dikembalikan atau rekod pustaka media</p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}/content</code></p><p class=\"note-s\"><code>GET /v1/media/assets</code></p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Pelan harga</h3><div class=\"card-result-process\" data-billing-basis><h5>Cara caj akhir dikira</h5><p class=\"note-s\">Kadar yang dipaparkan menganggarkan kos sebelum penjanaan. Caj akhir dikira berdasarkan kos yang direkodkan untuk penjanaan asal. Tempoh output yang diukur dan kuantiti ramalan bukan kuantiti akhir yang boleh dibilkan.</p></div><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Rujukan tarif tidak menambah pilihan permintaan. Parameter yang disokong disenaraikan untuk kaedah yang dipilih.</p><dl data-price-conditions><dt>Mod pantas</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila mod pantas dipilih</span></dd><dt>Mod flex</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila mod flex dipilih</span></dd><dt>Usaha penaakulan maksimum</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila usaha penaakulan maksimum menggunakan pelarasan default</span></dd></dl></div><div data-declared-tariff-pricing><h4>Anggaran kadar untuk perbandingan</h4><h4>Harga mengikut konfigurasi</h4><p class=\"note-s\">Padankan setiap caj dengan syarat yang dipaparkan. Gunakan satu kadar bagi setiap set konfigurasi alternatif.</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadual kadar</th><th>Kuantiti ramalan</th><th>Unit pengebilan</th><th>Caj</th></tr></thead><tbody><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Kadar asas token</th><td data-cell-label=\"Jadual kadar\"><span class=\"card-cell-label\">Jadual kadar</span>Kadar asas</td><td data-cell-label=\"Kuantiti ramalan\"><span class=\"card-cell-label\">Kuantiti ramalan</span>—</td><td data-cell-label=\"Unit pengebilan\"><span class=\"card-cell-label\">Unit pengebilan</span>—</td><td data-cell-label=\"Caj\"><span class=\"card-cell-label\">Caj</span><div><span>Input · Token input · Anggaran untuk perbandingan sahaja</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Output · Token output · Anggaran untuk perbandingan sahaja</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Bacaan cache · Anggaran untuk perbandingan sahaja</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache · Anggaran untuk perbandingan sahaja</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache, 1 jam · Anggaran untuk perbandingan sahaja</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>saat audio input</th><td data-cell-label=\"Jadual kadar\"><span class=\"card-cell-label\">Jadual kadar</span>—</td><td data-cell-label=\"Kuantiti ramalan\"><span class=\"card-cell-label\">Kuantiti ramalan</span>—</td><td data-cell-label=\"Unit pengebilan\"><span class=\"card-cell-label\">Unit pengebilan</span>bagi setiap saat audio masukan</td><td data-cell-label=\"Caj\"><span class=\"card-cell-label\">Caj</span><div><span>Input · saat audio input · Anggaran untuk perbandingan sahaja</span> <b>$0.00000666</b> <span class=\"price-unit\">bagi setiap saat audio masukan</span></div></td></tr><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Anggaran kos penjanaan</th><td data-cell-label=\"Jadual kadar\"><span class=\"card-cell-label\">Jadual kadar</span>—</td><td data-cell-label=\"Kuantiti ramalan\"><span class=\"card-cell-label\">Kuantiti ramalan</span>anggaran untuk satu penjanaan</td><td data-cell-label=\"Unit pengebilan\"><span class=\"card-cell-label\">Unit pengebilan</span>—</td><td data-cell-label=\"Caj\"><span class=\"card-cell-label\">Caj</span><div><span>Output · Anggaran kos penjanaan · Anggaran untuk perbandingan sahaja</span> <b>$0.00000666</b> <span class=\"price-unit\">anggaran sebelum penjanaan</span></div><p class=\"note-s\">Anggaran ini bukan caj tambahan atau kadar tetap bagi penjanaan yang telah selesai.</p></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. <a href=\"/docs/ms/billing/reserve/\">Cara rizab dan penyelesaian caj berfungsi →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Contoh permintaan</h3><h4>Ailoot Ultra · Transkripsi</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kod\"><button class=\"cg-tab\" id=\"model-code-2000-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2000-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · badan permintaan natif yang tepat dan hasil lengkap</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kod\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-2000-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2000-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\n: &quot;${AILOOT_AUDIO_FILE:?Set the path to your actual WAV recording}&quot;\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\nimport base64\naudio=Path(os.environ[&#39;AILOOT_AUDIO_FILE&#39;]).read_bytes()\nif not (audio[:4]==b&#39;RIFF&#39; and audio[8:12]==b&#39;WAVE&#39;): raise SystemExit(&#39;Supply an actual WAV audio file&#39;)\nif len(audio)&gt;26214400: raise SystemExit(&#39;Use a documented supported large-file flow&#39;)\nrequest={&#39;model&#39;: &#39;nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b&#39;, &#39;input_audio&#39;: {&#39;data&#39;: &#39;${BASE64_ACTUAL_WAV_BYTES}&#39;, &#39;format&#39;: &#39;wav&#39;}}\nrequest[&#39;input_audio&#39;][&#39;data&#39;]=base64.b64encode(audio).decode(&#39;ascii&#39;)\nPath(&#39;request.json&#39;).write_text(json.dumps(request,ensure_ascii=False),encoding=&#39;utf-8&#39;)\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Keep the complete original response and headers. Read every returned segment, word and usage field.\n# Preserve actual operation/task/asset IDs; continue reads of the original result without resubmitting.\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Terima dan simpan hasil</h3><h4>Ailoot Ultra · Transkripsi</h4><ul class=\"card-result-paths\"><li><code>GET /v1/media/tasks/{task_id}</code></li><li><code>GET /v1/media/assets/{asset_id}/content</code></li><li><code>GET /v1/media/assets</code></li><li><code>GET /v1/media/assets/{asset_id}</code></li></ul><details class=\"card-about\"><summary>Pembacaan kandungan lain</summary><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kod\"><button class=\"cg-tab\" id=\"model-code-2001-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2001-panel-0\" aria-selected=\"true\" tabindex=\"0\">Baca aset sedia ada yang menjadi milik anda</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kod\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-2001-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2001-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n</code></pre></div></div></div></details><div class=\"card-result-process\" data-all-results><h5>Simpan semua hasil yang selesai</h5><p class=\"note-s\">Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan.</p><p class=\"note-s\">Simpan respons dan pengepala yang lengkap, setiap output sebenar, pengecam asal yang dikembalikan serta semua medan penggunaan. Pulihkan operasi asal tanpa menghantar permintaan penciptaan sekali lagi.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Jika respons asal perlu disemak</h5><p class=\"note-s\">Simpan X-Client-Request-ID yang dikembalikan untuk penyelarasan rekod. Baca hanya nilai task_id/asset_id sebenar yang dikembalikan atau pustaka media milik anda; jangan sekali-kali bina URL tugas daripada ID operasi atau hantar semula permintaan penciptaan.</p></div><details class=\"card-about\" data-output-fields><summary>Medan respons</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Medan</th><th>Jenis</th></tr></thead><tbody><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">text</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span></td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span></td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">segments[]</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span></td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">words[]</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span></td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">speaker fields</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span></td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">timestamps</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span></td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Alias</h3><h4>Alias model</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=nvidia%2Fnemotron-3.5-asr-streaming-multilingual-0.6b&amp;route=Ultra&amp;caller=nvidia%2Fnemotron-3.5-asr-streaming-multilingual-0.6b&amp;fmt=transcriptions\"><code>nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b</code></a></span></p><h4>Alias laluan kaedah</h4><p class=\"note-s\">Gunakan laluan kaedah yang dipaparkan di atas.</p><h4>ID pemanggil berkaitan</h4><p class=\"note-s\"><a href=\"#m=nvidia%2Fnemotron-3.5-asr-streaming-multilingual-0.6b&amp;route=Ultra&amp;caller=nvidia%2Fnemotron-3.5-asr-streaming-multilingual-0.6b&amp;fmt=transcriptions\"><code>nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
        "fmt": "transcriptions",
        "http": "POST",
        "path": "/v1/audio/transcriptions",
        "request_model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|transcriptions|/v1/audio/transcriptions|nvidia%2Fnemotron-3.5-asr-streaming-multilingual-0.6b",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "billing_basis": {
          "basis": "original_invoice_usd",
          "description": "Kadar yang dipaparkan menganggarkan kos sebelum penjanaan. Caj akhir dikira berdasarkan kos yang direkodkan untuk penjanaan asal. Tempoh output yang diukur dan kuantiti ramalan bukan kuantiti akhir yang boleh dibilkan.",
          "forecast_quantity_is_estimate": true,
          "physical_output_is_billable_quantity": false,
          "version": "original_invoice_usd_v1"
        },
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "lifecycle": {
              "assets": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets"
                },
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}"
                }
              ],
              "content": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}/content",
                  "url_source": "exact returned signed URL; never construct token"
                }
              ],
              "mode": "synchronous_result_then_owned_library",
              "operation_id_is_not_task_id": true,
              "status": [
                {
                  "http": "GET",
                  "id_source": "actual returned task_id or media library record",
                  "path": "/v1/media/tasks/{task_id}"
                }
              ],
              "unknown": "Simpan X-Client-Request-ID yang dikembalikan untuk penyelarasan rekod. Baca hanya nilai task_id/asset_id sebenar yang dikembalikan atau pustaka media milik anda; jangan sekali-kali bina URL tugas daripada ID operasi atau hantar semula permintaan penciptaan."
            },
            "outputs": {
              "all_results": "Simpan respons dan pengepala yang lengkap, setiap output sebenar, pengecam asal yang dikembalikan serta semua medan penggunaan. Pulihkan operasi asal tanpa menghantar permintaan penciptaan sekali lagi.",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "text",
                  "type": null
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": null
                },
                {
                  "description": null,
                  "name": "segments[]",
                  "type": null
                },
                {
                  "description": null,
                  "name": "words[]",
                  "type": null
                },
                {
                  "description": null,
                  "name": "speaker fields",
                  "type": null
                },
                {
                  "description": null,
                  "name": "timestamps",
                  "type": null
                }
              ]
            },
            "parameters": [
              {
                "enum": [
                  "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "name": "input_audio",
                "required": true,
                "type": "object"
              },
              {
                "name": "language",
                "required": false,
                "type": "string"
              },
              {
                "maximum": 1,
                "minimum": 0,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "default": "json",
                "default_known": true,
                "enum": [
                  "json",
                  "verbose_json"
                ],
                "enum_known": true,
                "name": "response_format",
                "required": false,
                "type": "string"
              },
              {
                "items": {
                  "enum": [
                    "segment",
                    "word"
                  ],
                  "type": "string"
                },
                "name": "timestamp_granularities",
                "required": false,
                "type": "array"
              },
              {
                "name": "provider",
                "required": false,
                "type": "object"
              }
            ],
            "request_schema": {
              "properties": {
                "input_audio": {
                  "properties": {
                    "data": {
                      "contentEncoding": "base64",
                      "type": "string"
                    },
                    "format": {
                      "enum": [
                        "wav",
                        "mp3",
                        "flac",
                        "m4a",
                        "ogg",
                        "webm",
                        "aac"
                      ],
                      "type": "string"
                    }
                  },
                  "required": [
                    "data",
                    "format"
                  ],
                  "type": "object"
                },
                "language": {
                  "description": "ISO-639-1 code; omitted means auto-detection",
                  "type": "string"
                },
                "model": {
                  "enum": [
                    "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b"
                  ],
                  "type": "string"
                },
                "provider": {
                  "description": "Data policy and exact provider options; order/only/ignore are not applied to STT",
                  "properties": {
                    "data_collection": {
                      "enum": [
                        "allow",
                        "deny",
                        null
                      ],
                      "type": [
                        "string",
                        "null"
                      ]
                    },
                    "options": {
                      "type": "object"
                    },
                    "zdr": {
                      "type": [
                        "boolean",
                        "null"
                      ]
                    }
                  },
                  "type": "object"
                },
                "response_format": {
                  "default": "json",
                  "description": "verbose_json requires exact model/provider support",
                  "enum": [
                    "json",
                    "verbose_json"
                  ],
                  "type": "string"
                },
                "temperature": {
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                },
                "timestamp_granularities": {
                  "description": "Only used with supported verbose_json",
                  "items": {
                    "enum": [
                      "segment",
                      "word"
                    ],
                    "type": "string"
                  },
                  "type": "array"
                }
              },
              "required": [
                "model",
                "input_audio"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": true,
              "body": {
                "input_audio": {
                  "data": "${BASE64_ACTUAL_WAV_BYTES}",
                  "format": "wav"
                },
                "model": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_conditions": [
              "Baca fail WAV sebenar dan kodkan bait sebenarnya untuk input_audio JSON yang diisytiharkan; tiada laluan multipart ditawarkan bagi pengisytiharan tepat yang hanya menggunakan JSON ini."
            ],
            "material_types": [
              "audio"
            ],
            "required": [
              "model",
              "input_audio"
            ]
          },
          "lifecycle": {
            "assets": [
              {
                "http": "GET",
                "path": "/v1/media/assets"
              },
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}"
              }
            ],
            "content": [
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed URL; never construct token"
              }
            ],
            "mode": "synchronous_result_then_owned_library",
            "operation_id_is_not_task_id": true,
            "status": [
              {
                "http": "GET",
                "id_source": "task_id sebenar yang dikembalikan atau rekod pustaka media",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/audio/transcriptions"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "text",
            "fields": [
              {
                "description": null,
                "name": "text",
                "type": null
              },
              {
                "description": null,
                "name": "usage",
                "type": null
              },
              {
                "description": null,
                "name": "segments[]",
                "type": null
              },
              {
                "description": null,
                "name": "words[]",
                "type": null
              },
              {
                "description": null,
                "name": "speaker fields",
                "type": null
              },
              {
                "description": null,
                "name": "timestamps",
                "type": null
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          },
          {
            "basis": "Anggaran ini bukan caj tambahan atau kadar tetap bagi penjanaan yang telah selesai.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Anggaran kos penjanaan",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual WAV recording}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nimport base64\naudio=Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4]==b'RIFF' and audio[8:12]==b'WAVE'): raise SystemExit('Supply an actual WAV audio file')\nif len(audio)>26214400: raise SystemExit('Use a documented supported large-file flow')\nrequest={'model': 'nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b', 'input_audio': {'data': '${BASE64_ACTUAL_WAV_BYTES}', 'format': 'wav'}}\nrequest['input_audio']['data']=base64.b64encode(audio).decode('ascii')\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Keep the complete original response and headers. Read every returned segment, word and usage field.\n# Preserve actual operation/task/asset IDs; continue reads of the original result without resubmitting.\n",
            "label": "curl · exact native body and complete result",
            "language": "bash"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n",
            "label": "Read existing owned assets",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "transcriptions",
        "hints": [
          "Use the exact caller model ID and documented input representation.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "audio"
        ],
        "label": "Transkripsi",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "audio_transcriptions",
        "out": null,
        "output": [
          "text"
        ],
        "path": "/v1/audio/transcriptions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "original_invoice_usd",
          "image_input_price": null,
          "image_output_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          },
          {
            "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Estimated generation cost",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "request_model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
        "route_label": "Ultra",
        "status_reads": [
          "GET /v1/media/tasks/{task_id}"
        ],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "audio_input_second",
            "label": "input audio second",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "per input audio second",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "audio_input_second"
          },
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "forecast_usd",
            "label": "Estimated generation cost",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "estimate before generation",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "request_estimate"
          }
        ]
      }
    }
  ],
  "model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "126e317f134ea96249cc44070fa83e4f0bb4b420307930f6d1309e1db7e71e6a",
    "input_html_sha256": "463811e62ee5face0c51921612a1173ddb89a2121ca37a6e164949487a3cb5bc",
    "private_audit_sha256": "83df17d428a260a6f092e11dacd7455cbaf391e337c8cd783525651c3c492461",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/ms/nvidia-nemotron-3-5-asr-streaming-multilingual-0-6b/",
    "description": "Nemotron 3.5 ASR Streaming Multilingual 0.6B NVIDIA mentranskripsikan pertuturan menjadi teks bertanda baca menggunakan pengekod penstriman yang sedar cache. Model ini menyokong penyesuaian berdasarkan bahasa secara jelas atau pengesanan automatik, dengan 32 lokal sedia untuk transkripsi dan lapan memerlukan penyesuaian.",
    "locale": "ms",
    "md_url": "https://ailoot.ai/models/ms/nvidia-nemotron-3-5-asr-streaming-multilingual-0-6b/index.md",
    "title": "NVIDIA: Nemotron 3.5 ASR Streaming Multilingual 0.6B — Ailoot",
    "url": "https://ailoot.ai/models/ms/nvidia-nemotron-3-5-asr-streaming-multilingual-0-6b/"
  },
  "rawModel": {
    "about": "Nemotron 3.5 ASR Streaming Multilingual 0.6B ialah model pengecaman pertuturan NVIDIA dengan 600 juta parameter untuk transkripsi langsung dan beban kerja audio rakaman. Model ini memperluas barisan penstriman bahasa Inggeris dengan penyesuaian berdasarkan ID bahasa. Pertuturan menjadi teks dalam bahasa input, dengan tanda baca dan huruf besar terbina dalam output.\n\nLiputan bahasa pengeluar mempunyai tiga peringkat. Sembilan belas lokal sedia transkripsi meliputi bahasa Inggeris AS dan UK, Sepanyol AS dan Sepanyol, Perancis di Perancis dan Kanada, Itali, Portugis Brazil dan Portugal, Belanda, Jerman, Turki, Rusia, Arab, Hindi, Jepun, Korea, Vietnam dan Ukraine. Tiga belas lokal liputan luas menambah bahasa Poland, Sweden, Czech, Bokmål Norway, Denmark, Bulgaria, Finland, Croatia, Slovak, Mandarin, Hungary, Romania dan Estonia. Bersama-sama, 32 lokal ini menghasilkan transkripsi tanpa penalaan halus tambahan.\n\nLapan lokal sedia penyesuaian—bahasa Yunani, Lithuania, Latvia, Malta, Slovenia, Ibrani, Thai dan Nynorsk Norway—dikenali oleh tokenizer tetapi memerlukan penalaan halus dalam domain untuk mendayakan transkripsi penuh. Oleh itu, angka 40 lokal pengeluar bukan dakwaan bahawa kesemua empat puluh mempunyai keupayaan sedia guna yang sama. Checkpoint tersuai ialah artifak yang berasingan daripada model asas.\n\nSeni bina menggabungkan pengekod FastConformer 24 lapisan yang sedar cache dengan penyahkod RNN-T. Model ini mengekalkan keadaan perhatian dan konvolusi pengekod daripada bingkai terdahulu serta memproses setiap ketul audio baharu tanpa berulang kali mengira semula tetingkap bertindih. Isyarat ID bahasa dibekalkan bersama perwakilan akustik untuk menyesuaikan transkrip berdasarkan bahasa atau membiarkan model menyimpulkan bahasa.\n\nKonfigurasi NeMo NVIDIA mendokumenkan saiz ketul 80, 160, 320, 560 dan 1120 milisaat. Tetapan perhatian mengawal jumlah audio masa hadapan yang diterima ketul sebelum teks dikeluarkan, membolehkan tugas mengimbangkan masa menunggu dan konteks akustik. Ini ialah konfigurasi penstriman pengeluar, bukannya masa respons hujung ke hujung yang dijamin; pelaksanaan boleh mendedahkan subset sokongannya sendiri.\n\nSediakan audio WAV mono pada kadar sampel 16 kHz pemproses pengeluar. Apabila bahasa diketahui, gunakan penyesuaian berdasarkan lokal yang sepadan; mod automatik mengesan bahasa yang dituturkan. Contoh saluran asas menggunakan prom bahasa Inggeris AS secara lalai, maka tingkah laku berbilang bahasa perlu dikonfigurasi dengan sengaja dan bukannya diandaikan daripada contoh itu.\n\nDalam mod automatik, aliran kerja pengeluar boleh menambah tag bahasa selepas tanda baca penamat transkrip. Mengekalkan tag itu menyediakan bahasa kepada aplikasi yang mengendalikan trafik berbilang bahasa; membuangnya mengembalikan teks transkrip yang bersih. Kekalkan perbezaan antara perkataan yang dikenal pasti, tanda bacanya dan metadata bahasa ini apabila memaparkan atau memproses hasil.\n\nAplikasi kapsyen boleh membekalkan audio mengikut turutan, mengumpulkan transkrip dan menggunakan teks yang lengkap untuk paparan atau pemprosesan hiliran. Aplikasi suara boleh menghantar pertuturan yang dikenal pasti kepada peringkat pemahaman bahasanya. Kerja analisis panggilan boleh menyimpan rakaman asal dan transkrip bersama-sama supaya nama, nombor dan istilah tidak biasa kekal boleh disemak. Model ASR membekalkan transkrip; peringkasan, tindakan dan penjanaan pertuturan ialah peringkat aplikasi yang berasingan.\n\nNVIDIA melatih model pada campuran data pertuturan awam dan proprietari dengan label manusia serta sintetik yang dinormalkan kepada teks bertanda baca dan penggunaan huruf besar yang betul. Panduan penyesuaiannya menekankan pemadanan label bahasa dan gaya teks, kemudian penilaian audio yang diketepikan daripada latihan pada tetapan penstriman yang dimaksudkan untuk penggunaan. Ia menerangkan penyesuaian bahasa, loghat dan domain tanpa menjadikan hasil tersuai itu sifat checkpoint asal.\n\nKad model mengaitkan panjang rakaman praktikal dengan memori yang tersedia dan bukannya menerbitkan satu had tempoh sejagat. Bezakan edisi berbilang bahasa daripada model bahasa Inggeris sahaja, dan simpan bahasa terpilih serta konfigurasi penstriman bersama hasil transkripsi. Artifak output ialah teks yang dikenal pasti, dengan metadata bahasa pengeluar secara pilihan, dan bukannya jawapan perbualan umum.",
    "alias_of": null,
    "aliases": [],
    "author": "NVIDIA",
    "capabilities": {
      "context_length": 0,
      "manufacturer_input": [
        "audio"
      ],
      "manufacturer_output": [
        "transcription"
      ]
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "forecast_usd",
            "label": "Estimated generation cost",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "estimate before generation",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "request_estimate"
          }
        ],
        "summary": "Maklumat lengkap tentang harga konfigurasi terdapat dalam butiran."
      }
    ],
    "ctx": null,
    "formats": [
      "transcriptions"
    ],
    "id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
    "input": [
      "audio"
    ],
    "kind": "audio",
    "max_out": null,
    "methods": [
      {
        "available": null,
        "billing_basis": {
          "basis": "original_invoice_usd",
          "description": "Kadar yang dipaparkan menganggarkan kos sebelum penjanaan. Caj akhir dikira berdasarkan kos yang direkodkan untuk penjanaan asal. Tempoh output yang diukur dan kuantiti ramalan bukan kuantiti akhir yang boleh dibilkan.",
          "forecast_quantity_is_estimate": true,
          "physical_output_is_billable_quantity": false,
          "version": "original_invoice_usd_v1"
        },
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "lifecycle": {
              "assets": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets"
                },
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}"
                }
              ],
              "content": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}/content",
                  "url_source": "exact returned signed URL; never construct token"
                }
              ],
              "mode": "synchronous_result_then_owned_library",
              "operation_id_is_not_task_id": true,
              "status": [
                {
                  "http": "GET",
                  "id_source": "actual returned task_id or media library record",
                  "path": "/v1/media/tasks/{task_id}"
                }
              ],
              "unknown": "Simpan X-Client-Request-ID yang dikembalikan untuk penyelarasan rekod. Baca hanya nilai task_id/asset_id sebenar yang dikembalikan atau pustaka media milik anda; jangan sekali-kali bina URL tugas daripada ID operasi atau hantar semula permintaan penciptaan."
            },
            "outputs": {
              "all_results": "Simpan respons dan pengepala yang lengkap, setiap output sebenar, pengecam asal yang dikembalikan serta semua medan penggunaan. Pulihkan operasi asal tanpa menghantar permintaan penciptaan sekali lagi.",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "text",
                  "type": null
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": null
                },
                {
                  "description": null,
                  "name": "segments[]",
                  "type": null
                },
                {
                  "description": null,
                  "name": "words[]",
                  "type": null
                },
                {
                  "description": null,
                  "name": "speaker fields",
                  "type": null
                },
                {
                  "description": null,
                  "name": "timestamps",
                  "type": null
                }
              ]
            },
            "parameters": [
              {
                "enum": [
                  "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "name": "input_audio",
                "required": true,
                "type": "object"
              },
              {
                "name": "language",
                "required": false,
                "type": "string"
              },
              {
                "maximum": 1,
                "minimum": 0,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "default": "json",
                "default_known": true,
                "enum": [
                  "json",
                  "verbose_json"
                ],
                "enum_known": true,
                "name": "response_format",
                "required": false,
                "type": "string"
              },
              {
                "items": {
                  "enum": [
                    "segment",
                    "word"
                  ],
                  "type": "string"
                },
                "name": "timestamp_granularities",
                "required": false,
                "type": "array"
              },
              {
                "name": "provider",
                "required": false,
                "type": "object"
              }
            ],
            "request_schema": {
              "properties": {
                "input_audio": {
                  "properties": {
                    "data": {
                      "contentEncoding": "base64",
                      "type": "string"
                    },
                    "format": {
                      "enum": [
                        "wav",
                        "mp3",
                        "flac",
                        "m4a",
                        "ogg",
                        "webm",
                        "aac"
                      ],
                      "type": "string"
                    }
                  },
                  "required": [
                    "data",
                    "format"
                  ],
                  "type": "object"
                },
                "language": {
                  "description": "ISO-639-1 code; omitted means auto-detection",
                  "type": "string"
                },
                "model": {
                  "enum": [
                    "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b"
                  ],
                  "type": "string"
                },
                "provider": {
                  "description": "Data policy and exact provider options; order/only/ignore are not applied to STT",
                  "properties": {
                    "data_collection": {
                      "enum": [
                        "allow",
                        "deny",
                        null
                      ],
                      "type": [
                        "string",
                        "null"
                      ]
                    },
                    "options": {
                      "type": "object"
                    },
                    "zdr": {
                      "type": [
                        "boolean",
                        "null"
                      ]
                    }
                  },
                  "type": "object"
                },
                "response_format": {
                  "default": "json",
                  "description": "verbose_json requires exact model/provider support",
                  "enum": [
                    "json",
                    "verbose_json"
                  ],
                  "type": "string"
                },
                "temperature": {
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                },
                "timestamp_granularities": {
                  "description": "Only used with supported verbose_json",
                  "items": {
                    "enum": [
                      "segment",
                      "word"
                    ],
                    "type": "string"
                  },
                  "type": "array"
                }
              },
              "required": [
                "model",
                "input_audio"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": true,
              "body": {
                "input_audio": {
                  "data": "${BASE64_ACTUAL_WAV_BYTES}",
                  "format": "wav"
                },
                "model": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_conditions": [
              "Baca fail WAV sebenar dan kodkan bait sebenarnya untuk input_audio JSON yang diisytiharkan; tiada laluan multipart ditawarkan bagi pengisytiharan tepat yang hanya menggunakan JSON ini."
            ],
            "material_types": [
              "audio"
            ],
            "required": [
              "model",
              "input_audio"
            ]
          },
          "lifecycle": {
            "assets": [
              {
                "http": "GET",
                "path": "/v1/media/assets"
              },
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}"
              }
            ],
            "content": [
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed URL; never construct token"
              }
            ],
            "mode": "synchronous_result_then_owned_library",
            "operation_id_is_not_task_id": true,
            "status": [
              {
                "http": "GET",
                "id_source": "task_id sebenar yang dikembalikan atau rekod pustaka media",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/audio/transcriptions"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "text",
            "fields": [
              {
                "description": null,
                "name": "text",
                "type": null
              },
              {
                "description": null,
                "name": "usage",
                "type": null
              },
              {
                "description": null,
                "name": "segments[]",
                "type": null
              },
              {
                "description": null,
                "name": "words[]",
                "type": null
              },
              {
                "description": null,
                "name": "speaker fields",
                "type": null
              },
              {
                "description": null,
                "name": "timestamps",
                "type": null
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          },
          {
            "basis": "Anggaran ini bukan caj tambahan atau kadar tetap bagi penjanaan yang telah selesai.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Anggaran kos penjanaan",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual WAV recording}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nimport base64\naudio=Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4]==b'RIFF' and audio[8:12]==b'WAVE'): raise SystemExit('Supply an actual WAV audio file')\nif len(audio)>26214400: raise SystemExit('Use a documented supported large-file flow')\nrequest={'model': 'nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b', 'input_audio': {'data': '${BASE64_ACTUAL_WAV_BYTES}', 'format': 'wav'}}\nrequest['input_audio']['data']=base64.b64encode(audio).decode('ascii')\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Keep the complete original response and headers. Read every returned segment, word and usage field.\n# Preserve actual operation/task/asset IDs; continue reads of the original result without resubmitting.\n",
            "label": "curl · exact native body and complete result",
            "language": "bash"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n",
            "label": "Read existing owned assets",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "transcriptions",
        "hints": [
          "Use the exact caller model ID and documented input representation.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "audio"
        ],
        "label": "Transkripsi",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "audio_transcriptions",
        "out": null,
        "output": [
          "text"
        ],
        "path": "/v1/audio/transcriptions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "original_invoice_usd",
          "image_input_price": null,
          "image_output_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          },
          {
            "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Estimated generation cost",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "request_model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
        "route_label": "Ultra",
        "status_reads": [
          "GET /v1/media/tasks/{task_id}"
        ],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "audio_input_second",
            "label": "input audio second",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "per input audio second",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "audio_input_second"
          },
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "forecast_usd",
            "label": "Estimated generation cost",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "estimate before generation",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "request_estimate"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
        "request_model_id": "nvidia/nemotron-3.5-asr-streaming-multilingual-0.6b",
        "route_label": "Ultra"
      }
    ],
    "name": "NVIDIA: Nemotron 3.5 ASR Streaming Multilingual 0.6B",
    "price": {
      "estimate_only": true,
      "in": null,
      "in_label": null,
      "out": 6.66e-06,
      "out_label": "estimate before generation",
      "scope_label": "Estimated generation cost",
      "sort_in": null,
      "sort_out": 6.66e-06,
      "varies": false
    },
    "short": "Nemotron 3.5 ASR Streaming Multilingual 0.6B NVIDIA mentranskripsikan pertuturan menjadi teks bertanda baca menggunakan pengekod penstriman yang sedar cache. Model ini menyokong penyesuaian berdasarkan bahasa secara jelas atau pengesanan automatik, dengan 32 lokal sedia untuk transkripsi dan lapan memerlukan penyesuaian."
  },
  "renderer_schema": {
    "method_order": "Original DTO methods order; every exact route/format/path/caller survives.",
    "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers."
  },
  "representation": "exact-public-dto-and-native-renderer-html",
  "representationNotes": {
    "current_reference": {
      "about_json_pointer": "/aboutHtml",
      "methods": [
        {
          "contract_json_pointer": "/methods/0/rawMethod/contract",
          "html_json_pointer": "/methods/0/html",
          "method_ordinal": 0
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Nemotron 3.5 ASR Streaming Multilingual 0.6B NVIDIA mentranskripsikan pertuturan menjadi teks bertanda baca menggunakan pengekod penstriman yang sedar cache. Model ini menyokong penyesuaian berdasarkan bahasa secara jelas atau pengesanan automatik, dengan 32 lokal sedia untuk transkripsi dan lapan memerlukan penyesuaian.",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "8f6fe91ba2a5dafb972e04487de800baadd044e07267e42478be5ad52d91bfd2",
    "renderer_sha256": "1dab5ba62521e9568c8b7c82005622cabbf330a075df7cce1f83274a04009460"
  },
  "sourceRevision": "c3373147f969dd658d70cab6cce60cd81962e5a7d32e142c5baeaec035e3824b"
}