Nemotron Asr Multilingual
Integrer
nvidia/nemotron-asr-multilingual/asr
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/nvidia/nemotron-asr-multilingual/asr?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/nvidia/nemotron-asr-multilingual/asr?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nvidia/nemotron-asr-multilingual/asr", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/da/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "nvidia/nemotron-asr-multilingual/asr",
"input": {
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
}
Kald Nemotron Asr Multilingual-modellen (nvidia/nemotron-asr-multilingual/asr) via Doitong API. Dokumentation til agenter: https://doitong.com/da/developers/models/nvidia/nemotron-asr-multilingual/asr.md
POST https://api.doitong.ru/v1/run/nvidia/nemotron-asr-multilingual/asr?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
Hvis svarstatus er "queued" eller "running", skal du forespørge GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 igen, indtil den er "succeeded"; filerne findes i outputs[].url. POST https://api.doitong.ru/v1/quote/nvidia/nemotron-asr-multilingual/asr med samme body returnerer den nøjagtige pris før kørslen.
Filer som eksemplet: 0,002 $ 2 API-kreditter · ≈ 0,22 ₽ dine filer måles før kørslen Kør den på denne side
Din nye API-nøgle. Den vises kun nu og findes allerede i koden og i feltet til API-nøglen nedenfor. Hold den hemmelig: Anbring den aldrig i kode, der kører i en browser.
Dit første resultat kommer her
Opret en anmodning nedenfor, og kør den med din API-nøgle. Output kopieres til vores lagring, gemt for altid eller 7 dage gratis.
Opret en anmodning
Kontrollerne genereres fra modellens skema. Koden og prisen opdateres, når du ændrer dem.
/run/nvidia/nemotron-asr-multilingual/asr?wait=20
pris → 0,002 $
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/nvidia/nemotron-asr-multilingual/asr?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/nvidia/nemotron-asr-multilingual/asr?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nvidia/nemotron-asr-multilingual/asr", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "nvidia/nemotron-asr-multilingual/asr",
"input": {
"audio": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
},
"wait_seconds": 20
}
}
}
Kør denne anmodning
Din nøgle forbliver i denne browser: Den sendes kun til Doitong API og gemmes kun i localStorage, hvis du markerer Husk. Hent en API-nøgle
Om Nemotron Asr Multilingual
Transskriberer en lydfil fra `audio_url` til tekst. Inputtet `language` er som standard `auto` for detektion, eller du kan vælge en lokalitet som en-US, de-DE eller ja-JP fra listen. `acceleration` afvejer nøjagtighed mod hastighed: `none` er mest nøjagtig, `regular` er afbalanceret, `high` er hurtigere, og `full` er hurtigst.
Parametre
Send enten det kanoniske navn eller det oprindelige navn, ikke begge. Kanoniske navne
audio_urlpåkrævet
audio
languagevalgfri
+25 flere
zh-CNvi-VNhe-ILnl-NLcs-CZda-DKpl-PLnn-NOnb-NOsv-SEth-THtr-TRbg-BGel-GRet-EEfi-FIhr-HRhu-HUlt-LTlv-LVro-ROsk-SKuk-UAmt-MTsl-SIaccelerationvalgfri
Filparametre accepterer en offentlig https://-URL, en data:-URI på op til 10 MB eller file_url fra en upload. Filer
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "nvidia/nemotron-asr-multilingual/asr",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 2,
"usd": "0.002",
"charged": 2,
"refunded": 0
},
"input": {
"audio_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
},
"output": {
"output": "Actually, I'm second guessing myself a single coherent passage might be cleaner and more representative of real world speech performance, which is what benchmarking typically uses. I'll write an engaging flowing piece on something like a journey or a day in a tech forward city. That weaves in all the varied elements naturally, rather than splitting it into sections. I'm deciding to keep the targeted tricky sentences section after all. It'll directly test homophones and number heavy lines that are most prone to errors, so I'll include it as a concise, clearly marked addition at the end now. I'm drafting the full passage, starting with a detailed travel narrative that weaves in dates, times, currency, and specific details by the time we pulled into Waverley Station, my phone had buzzed forty seven times, mostly from doctor Amara Akon Reyes at Neurosynt Technologies fretting over our board presentation. We'd spent three weeks refining a transformer model with one point three billion parameters, and the improvements were stunning. Our word error rate plummeted from fourteen point two percent down to three point eight percent. There's something surreal about watching those number shift like that. They're not just metrics they're the payoff from countless late nights and too much coffee.",
"partial": false
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Outputfelter
- output
- stringTekst opnået ved transskription af lyden.
- partial
- booleanTrue, når streamingresultatet er mellemliggende.
Flere modeller: Tale til tekst
Til AI-agenter: Denne side som Markdown findes på https://doitong.com/da/developers/models/nvidia/nemotron-asr-multilingual/asr.md. Alle modeller og vejledninger: https://doitong.com/developers/llms.txt