Update API inference documentation (automated)

Author: Wauplin

docs/api-inference/tasks/audio-classification.md

@@ -40,54 +40,21 @@ 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 \
-	-X POST \
-	--data-binary '@sample1.flac' \
-	-H "Authorization: Bearer hf_***"
+[object Object]
 ```
 </curl>
 
 <python>
 ```py
-import requests
-
-API_URL = "https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition"
-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()
-
-output = query("sample1.flac")
+[object Object]
 ```
 
 To use the Python client, see `huggingface_hub`'s [package reference](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient.audio_classification).
 </python>
 
 <js>
 ```js
-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",
-		{
-			headers: {
-				Authorization: "Bearer hf_***"
-				"Content-Type": "application/json",
-			},
-			method: "POST",
-			body: data,
-		}
-	);
-	const result = await response.json();
-	return result;
-}
-
-query("sample1.flac").then((response) => {
-	console.log(JSON.stringify(response));
-});
+[object Object]
 ```
 
 To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#audioclassification).

docs/api-inference/tasks/automatic-speech-recognition.md

@@ -41,54 +41,21 @@ 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 \
-	-X POST \
-	--data-binary '@sample1.flac' \
-	-H "Authorization: Bearer hf_***"
+[object Object]
 ```
 </curl>
 
 <python>
 ```py
-import requests
-
-API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3"
-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()
-
-output = query("sample1.flac")
+[object Object]
 ```
 
 To use the Python client, see `huggingface_hub`'s [package reference](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient.automatic_speech-recognition).
 </python>
 
 <js>
 ```js
-async function query(filename) {
-	const data = fs.readFileSync(filename);
-	const response = await fetch(
-		"https://api-inference.huggingface.co/models/openai/whisper-large-v3",
-		{
-			headers: {
-				Authorization: "Bearer hf_***"
-				"Content-Type": "application/json",
-			},
-			method: "POST",
-			body: data,
-		}
-	);
-	const result = await response.json();
-	return result;
-}
-
-query("sample1.flac").then((response) => {
-	console.log(JSON.stringify(response));
-});
+[object Object]
 ```
 
 To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#automaticspeech-recognition).

docs/api-inference/tasks/chat-completion.md

@@ -61,50 +61,21 @@ The API supports:
 
 <curl>
 ```bash
-curl 'https://api-inference.huggingface.co/models/google/gemma-2-2b-it/v1/chat/completions' \
--H "Authorization: Bearer hf_***" \
--H 'Content-Type: application/json' \
--d '{
-	"model": "google/gemma-2-2b-it",
-	"messages": [{"role": "user", "content": "What is the capital of France?"}],
-	"max_tokens": 500,
-	"stream": false
-}'
-
+[object Object]
 ```
 </curl>
 
 <python>
 ```py
-from huggingface_hub import InferenceClient
-
-client = InferenceClient(api_key="hf_***")
-
-for message in client.chat_completion(
-	model="google/gemma-2-2b-it",
-	messages=[{"role": "user", "content": "What is the capital of France?"}],
-	max_tokens=500,
-	stream=True,
-):
-    print(message.choices[0].delta.content, end="")
+[object Object],[object Object]
 ```
 
 To use the Python client, see `huggingface_hub`'s [package reference](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient.chat_completion).
 </python>
 
 <js>
 ```js
-import { HfInference } from "@huggingface/inference";
-
-const inference = new HfInference("hf_***");
-
-for await (const chunk of inference.chatCompletionStream({
-	model: "google/gemma-2-2b-it",
-	messages: [{ role: "user", content: "What is the capital of France?" }],
-	max_tokens: 500,
-})) {
-	process.stdout.write(chunk.choices[0]?.delta?.content || "");
-}
+[object Object],[object Object]
 ```
 
 To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#chatcompletion).
@@ -121,77 +92,21 @@ To use the JavaScript client, see `huggingface.js`'s [package reference](https:/
 
 <curl>
 ```bash
-curl 'https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-11B-Vision-Instruct/v1/chat/completions' \
--H "Authorization: Bearer hf_***" \
--H 'Content-Type: application/json' \
--d '{
-	"model": "meta-llama/Llama-3.2-11B-Vision-Instruct",
-	"messages": [
-		{
-			"role": "user",
-			"content": [
-				{"type": "image_url", "image_url": {"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"}},
-				{"type": "text", "text": "Describe this image in one sentence."}
-			]
-		}
-	],
-	"max_tokens": 500,
-	"stream": false
-}'
-
+[object Object]
 ```
 </curl>
 
 <python>
 ```py
-from huggingface_hub import InferenceClient
-
-client = InferenceClient(api_key="hf_***")
-
-image_url = "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
-
-for message in client.chat_completion(
-	model="meta-llama/Llama-3.2-11B-Vision-Instruct",
-	messages=[
-		{
-			"role": "user",
-			"content": [
-				{"type": "image_url", "image_url": {"url": image_url}},
-				{"type": "text", "text": "Describe this image in one sentence."},
-			],
-		}
-	],
-	max_tokens=500,
-	stream=True,
-):
-	print(message.choices[0].delta.content, end="")
+[object Object],[object Object]
 ```
 
 To use the Python client, see `huggingface_hub`'s [package reference](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient.chat_completion).
 </python>
 
 <js>
 ```js
-import { HfInference } from "@huggingface/inference";
-
-const inference = new HfInference("hf_***");
-const imageUrl = "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg";
-
-for await (const chunk of inference.chatCompletionStream({
-	model: "meta-llama/Llama-3.2-11B-Vision-Instruct",
-	messages: [
-		{
-			"role": "user",
-			"content": [
-				{"type": "image_url", "image_url": {"url": imageUrl}},
-				{"type": "text", "text": "Describe this image in one sentence."},
-			],
-		}
-	],
-	max_tokens: 500,
-})) {
-	process.stdout.write(chunk.choices[0]?.delta?.content || "");
-}
+[object Object],[object Object]
 ```
 
 To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#chatcompletion).

docs/api-inference/tasks/feature-extraction.md

@@ -40,54 +40,21 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <curl>
 ```bash
-curl https://api-inference.huggingface.co/models/thenlper/gte-large \
-	-X POST \
-	-d '{"inputs": "Today is a sunny day and I will get some ice cream."}' \
-	-H 'Content-Type: application/json' \
-	-H "Authorization: Bearer hf_***"
+[object Object]
 ```
 </curl>
 
 <python>
 ```py
-import requests
-
-API_URL = "https://api-inference.huggingface.co/models/thenlper/gte-large"
-headers = {"Authorization": "Bearer hf_***"}
-
-def query(payload):
-	response = requests.post(API_URL, headers=headers, json=payload)
-	return response.json()
-	
-output = query({
-	"inputs": "Today is a sunny day and I will get some ice cream.",
-})
+[object Object]
 ```
 
 To use the Python client, see `huggingface_hub`'s [package reference](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient.feature_extraction).
 </python>
 
 <js>
 ```js
-async function query(data) {
-	const response = await fetch(
-		"https://api-inference.huggingface.co/models/thenlper/gte-large",
-		{
-			headers: {
-				Authorization: "Bearer hf_***"
-				"Content-Type": "application/json",
-			},
-			method: "POST",
-			body: JSON.stringify(data),
-		}
-	);
-	const result = await response.json();
-	return result;
-}
-
-query({"inputs": "Today is a sunny day and I will get some ice cream."}).then((response) => {
-	console.log(JSON.stringify(response));
-});
+[object Object]
 ```
 
 To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#featureextraction).

docs/api-inference/tasks/fill-mask.md

@@ -36,54 +36,21 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <curl>
 ```bash
-curl https://api-inference.huggingface.co/models/google-bert/bert-base-uncased \
-	-X POST \
-	-d '{"inputs": "The answer to the universe is [MASK]."}' \
-	-H 'Content-Type: application/json' \
-	-H "Authorization: Bearer hf_***"
+[object Object]
 ```
 </curl>
 
 <python>
 ```py
-import requests
-
-API_URL = "https://api-inference.huggingface.co/models/google-bert/bert-base-uncased"
-headers = {"Authorization": "Bearer hf_***"}
-
-def query(payload):
-	response = requests.post(API_URL, headers=headers, json=payload)
-	return response.json()
-	
-output = query({
-	"inputs": "The answer to the universe is [MASK].",
-})
+[object Object]
 ```
 
 To use the Python client, see `huggingface_hub`'s [package reference](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient.fill_mask).
 </python>
 
 <js>
 ```js
-async function query(data) {
-	const response = await fetch(
-		"https://api-inference.huggingface.co/models/google-bert/bert-base-uncased",
-		{
-			headers: {
-				Authorization: "Bearer hf_***"
-				"Content-Type": "application/json",
-			},
-			method: "POST",
-			body: JSON.stringify(data),
-		}
-	);
-	const result = await response.json();
-	return result;
-}
-
-query({"inputs": "The answer to the universe is [MASK]."}).then((response) => {
-	console.log(JSON.stringify(response));
-});
+[object Object]
 ```
 
 To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#fillmask).