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Fix snippet + generate from @huggingface/inference #1624

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merged 2 commits into from
Mar 5, 2025
Merged

Fix snippet + generate from @huggingface/inference #1624

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4a7d3da
Fix snippet + generate from @huggingface/inference
Wauplin Mar 4, 2025
e8050d4
dummy
Wauplin Mar 4, 2025
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16 changes: 9 additions & 7 deletions docs/api-inference/tasks/audio-classification.md
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,9 @@ For more details about the `audio-classification` task, check out its [dedicated

### Recommended models

- [speechbrain/google_speech_command_xvector](https://huggingface.co/speechbrain/google_speech_command_xvector): An easy-to-use model for command recognition.
- [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition): An emotion recognition model.
- [facebook/mms-lid-126](https://huggingface.co/facebook/mms-lid-126): A language identification model.

Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=audio-classification&sort=trending).

Expand All @@ -40,7 +42,7 @@ Explore all available models and find the one that suits you best [here](https:/

<curl>
```bash
curl https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition \
curl https://router.huggingface.co/hf-inference/models/speechbrain/google_speech_command_xvector \
-X POST \
--data-binary '@sample1.flac' \
-H 'Authorization: Bearer hf_***'
Expand All @@ -51,14 +53,14 @@ curl https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-
```py
import requests

API_URL = "https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition"
API_URL = "https://router.huggingface.co/hf-inference/v1"
headers = {"Authorization": "Bearer hf_***"}

def query(filename):
with open(filename, "rb") as f:
data = f.read()
response = requests.post(API_URL, headers=headers, data=data)
return response.json()
with open(filename, "rb") as f:
data = f.read()
response = requests.post(API_URL, headers=headers, data=data)
return response.json()

output = query("sample1.flac")
```
Expand All @@ -71,7 +73,7 @@ To use the Python client, see `huggingface_hub`'s [package reference](https://hu
async function query(filename) {
const data = fs.readFileSync(filename);
const response = await fetch(
"https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition",
"https://router.huggingface.co/hf-inference/models/speechbrain/google_speech_command_xvector",
{
headers: {
Authorization: "Bearer hf_***",
Expand Down
37 changes: 28 additions & 9 deletions docs/api-inference/tasks/automatic-speech-recognition.md
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Expand Up @@ -30,7 +30,7 @@ For more details about the `automatic-speech-recognition` task, check out its [d
### Recommended models

- [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3): A powerful ASR model by OpenAI.
- [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1): Powerful speaker diarization model.
- [facebook/seamless-m4t-v2-large](https://huggingface.co/facebook/seamless-m4t-v2-large): An end-to-end model that performs ASR and Speech Translation by MetaAI.

Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=automatic-speech-recognition&sort=trending).

Expand All @@ -41,7 +41,7 @@ Explore all available models and find the one that suits you best [here](https:/

<curl>
```bash
curl https://api-inference.huggingface.co/models/openai/whisper-large-v3 \
curl https://router.huggingface.co/hf-inference/models/openai/whisper-large-v3 \
-X POST \
--data-binary '@sample1.flac' \
-H 'Authorization: Bearer hf_***'
Expand All @@ -52,14 +52,14 @@ curl https://api-inference.huggingface.co/models/openai/whisper-large-v3 \
```py
import requests

API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3"
API_URL = "https://router.huggingface.co/hf-inference/v1"
headers = {"Authorization": "Bearer hf_***"}

def query(filename):
with open(filename, "rb") as f:
data = f.read()
response = requests.post(API_URL, headers=headers, data=data)
return response.json()
with open(filename, "rb") as f:
data = f.read()
response = requests.post(API_URL, headers=headers, data=data)
return response.json()

output = query("sample1.flac")
```
Expand All @@ -68,11 +68,30 @@ To use the Python client, see `huggingface_hub`'s [package reference](https://hu
</python>

<js>
Using `huggingface.js`:
```js
import { HfInference } from "@huggingface/inference";

const client = new HfInference("hf_***");

const data = fs.readFileSync("sample1.flac");

const output = await client.automaticSpeechRecognition({
data,
model: "openai/whisper-large-v3",
provider: "hf-inference",
});

console.log(output);

```

Using `fetch`:
```js
async function query(filename) {
const data = fs.readFileSync(filename);
const response = await fetch(
"https://api-inference.huggingface.co/models/openai/whisper-large-v3",
"https://router.huggingface.co/hf-inference/models/openai/whisper-large-v3",
{
headers: {
Authorization: "Bearer hf_***",
Expand Down Expand Up @@ -143,5 +162,5 @@ For more information about Inference API headers, check out the parameters [guid
| **text** | _string_ | The recognized text. |
| **chunks** | _object[]_ | When returnTimestamps is enabled, chunks contains a list of audio chunks identified by the model. |
| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;text** | _string_ | A chunk of text identified by the model |
| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;timestamps** | _number[]_ | The start and end timestamps corresponding with the text |
| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;timestamp** | _number[]_ | The start and end timestamps corresponding with the text |

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