Merge branch 'Vaibhavs10-patch-1' of https://github.com/huggingface/h…

…ub-docs into Vaibhavs10-patch-1
huggingface · Nov 29, 2024 · 141bb3d · 141bb3d
2 parents 275d327 + a25f324
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diff --git a/.github/workflows/api_inference_generate_documentation.yml b/.github/workflows/api_inference_generate_documentation.yml
@@ -0,0 +1,64 @@
+name: Update API Inference Documentation
+
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: "0 3 * * *" # Every day at 3am
+
+concurrency:
+  group: api_inference_generate_documentation
+  cancel-in-progress: true
+
+jobs:
+  pull_request:
+    runs-on: ubuntu-latest
+    steps:
+      # Setup
+      - uses: actions/checkout@v3
+      - uses: actions/setup-node@v3
+        with:
+          node-version: "20"
+      - name: Install pnpm
+        uses: pnpm/action-setup@v2
+        with:
+          run_install: |
+            - recursive: true
+              cwd: ./scripts/api-inference
+              args: [--frozen-lockfile]
+          package_json_file: ./scripts/api-inference/package.json
+      - name: Update huggingface/tasks package
+        working-directory: ./scripts/api-inference
+        run: |
+          pnpm update @huggingface/tasks@latest
+      # Generate
+      - name: Generate API inference documentation
+        run: pnpm run generate
+        working-directory: ./scripts/api-inference
+
+      # Check changes
+      - name: Check changes
+        run: git status
+
+      # Create or update Pull Request
+      - name: Create Pull Request
+        uses: peter-evans/create-pull-request@v7
+        with:
+          token: ${{ secrets.TOKEN_INFERENCE_SYNC_BOT }}
+          commit-message: Update API inference documentation (automated)
+          branch: update-api-inference-docs-automated-pr
+          delete-branch: true
+          title: "[Bot] Update API inference documentation"
+          body: |
+            This PR automatically upgrades the `@huggingface/tasks` package and regenerates the API inference documentation by running:
+            ```sh
+            cd scripts/api-inference
+            pnpm update @huggingface/tasks@latest
+            pnpm run generate
+            ```
+            
+            This PR was automatically created by the [Update API Inference Documentation workflow](https://github.com/huggingface/hub-docs/blob/main/.github/workflows/api_inference_generate_documentation.yml).
+            
+            Please review the changes before merging.
+          reviewers: |
+            Wauplin
+            hanouticelina
diff --git a/docs/api-inference/_toctree.yml b/docs/api-inference/_toctree.yml
@@ -30,6 +30,8 @@
       title: Image Segmentation
     - local: tasks/image-to-image
       title: Image to Image
+    - local: tasks/image-text-to-text
+      title: Image-Text to Text
     - local: tasks/object-detection
       title: Object Detection
     - local: tasks/question-answering

diff --git a/docs/api-inference/index.md b/docs/api-inference/index.md
@@ -46,8 +46,16 @@ The documentation is organized into two sections:
 
 ---
 
-## Looking for custom support from the Hugging Face team?
+## Inference Playground
 
-<a target="_blank" href="https://huggingface.co/support">
-    <img alt="HuggingFace Expert Acceleration Program" src="https://cdn-media.huggingface.co/marketing/transformers/new-support-improved.png" style="max-width: 600px; border: 1px solid #eee; border-radius: 4px; box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);">
+If you want to get started quickly with [Chat Completion models](https://huggingface.co/models?inference=warm&other=conversational&sort=trending) use the Inference Playground to quickly text and compare models against your prompts.
+
+<a href="https://huggingface.co/playground" target="blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/5f17f0a0925b9863e28ad517/9_Tgf0Tv65srhBirZQMTp.png" style="max-width: 550px; width: 100%;"/></a>
+
+---
+
+## Serious about AI in your organisation? Build faster with the Hugging Face Enterprise Hub.
+
+<a target="_blank" href="https://huggingface.co/enterprise">
+    <img alt="Hugging Face Enterprise Hub" src="https://cdn-uploads.huggingface.co/production/uploads/5f17f0a0925b9863e28ad517/64zNL-65xyIpRqWHe2iD0.png" style="width: 100%; max-width: 550px; border: 1px solid #eee; border-radius: 4px; box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);">
 </a><br>
diff --git a/docs/api-inference/rate-limits.md b/docs/api-inference/rate-limits.md
@@ -4,8 +4,10 @@ The Inference API has rate limits based on the number of requests. These rate li
 
 Serverless API is not meant to be used for heavy production applications. If you need higher rate limits, consider [Inference Endpoints](https://huggingface.co/docs/inference-endpoints) to have dedicated resources.
 
+You need to be authenticated (passing a token or through your browser) to use the Inference API.
+
+
 | User Tier           | Rate Limit                |
 |---------------------|---------------------------|
-| Unregistered Users  | 1 request per hour        |
-| Signed-up Users     | 50 requests per hour     |
-| PRO and Enterprise Users           | 500 requests per hour    |
+| Signed-up Users     | 1,000 requests per day     |
+| PRO and Enterprise Users           | 20,000 requests per day    |
diff --git a/docs/api-inference/tasks/audio-classification.md b/docs/api-inference/tasks/audio-classification.md
@@ -29,8 +29,9 @@ For more details about the `audio-classification` task, check out its [dedicated
 
 ### Recommended models
 
+- [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition): An emotion recognition model.
 
-This is only a subset of the supported models. Find the model that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=audio-classification&sort=trending).
+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).
 
 ### Using the API
 
@@ -39,19 +40,18 @@ This is only a subset of the supported models. Find the model that suits you bes
 
 <curl>
 ```bash
-curl https://api-inference.huggingface.co/models/<REPO_ID> \
+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_***"
-
 ```
 </curl>
 
 <python>
 ```py
 import requests
 
-API_URL = "https://api-inference.huggingface.co/models/<REPO_ID>"
+API_URL = "https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition"
 headers = {"Authorization": "Bearer hf_***"}
 
 def query(filename):
@@ -71,7 +71,7 @@ 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/<REPO_ID>",
+		"https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition",
 		{
 			headers: {
 				Authorization: "Bearer hf_***"
@@ -104,7 +104,7 @@ To use the JavaScript client, see `huggingface.js`'s [package reference](https:/
 | Payload |  |  |
 | :--- | :--- | :--- |
 | **inputs*** | _string_ | The input audio data as a base64-encoded string. If no `parameters` are provided, you can also provide the audio data as a raw bytes payload. |
-| **parameters** | _object_ | Additional inference parameters for Audio Classification |
+| **parameters** | _object_ |  |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;function_to_apply** | _enum_ | Possible values: sigmoid, softmax, none. |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;top_k** | _integer_ | When specified, limits the output to the top K most probable classes. |
 

diff --git a/docs/api-inference/tasks/automatic-speech-recognition.md b/docs/api-inference/tasks/automatic-speech-recognition.md
@@ -32,7 +32,7 @@ For more details about the `automatic-speech-recognition` task, check out its [d
 - [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.
 
-This is only a subset of the supported models. Find the model that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=automatic-speech-recognition&sort=trending).
+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).
 
 ### Using the API
 
@@ -45,7 +45,6 @@ curl https://api-inference.huggingface.co/models/openai/whisper-large-v3 \
 	-X POST \
 	--data-binary '@sample1.flac' \
 	-H "Authorization: Bearer hf_***"
-
 ```
 </curl>
 
@@ -65,7 +64,7 @@ def query(filename):
 output = query("sample1.flac")
 ```
 
-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).
+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>
@@ -92,7 +91,7 @@ query("sample1.flac").then((response) => {
 });
 ```
 
-To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#automaticspeech-recognition).
+To use the JavaScript client, see `huggingface.js`'s [package reference](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#automaticspeechrecognition).
 </js>
 
 </inferencesnippet>
@@ -106,9 +105,9 @@ To use the JavaScript client, see `huggingface.js`'s [package reference](https:/
 | Payload |  |  |
 | :--- | :--- | :--- |
 | **inputs*** | _string_ | The input audio data as a base64-encoded string. If no `parameters` are provided, you can also provide the audio data as a raw bytes payload. |
-| **parameters** | _object_ | Additional inference parameters for Automatic Speech Recognition |
+| **parameters** | _object_ |  |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;return_timestamps** | _boolean_ | Whether to output corresponding timestamps with the generated text |
-| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;generate** | _object_ | Ad-hoc parametrization of the text generation process |
+| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;generation_parameters** | _object_ |  |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;temperature** | _number_ | The value used to modulate the next token probabilities. |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;top_k** | _integer_ | The number of highest probability vocabulary tokens to keep for top-k-filtering. |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;top_p** | _number_ | If set to float < 1, only the smallest set of most probable tokens with probabilities that add up to top_p or higher are kept for generation. |