[Inference Providers] Fix generate + more instructions for providers documentation

docs/inference-providers/providers/cohere.md

@@ -56,6 +56,6 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"cohere":{"modelId":"CohereLabs/aya-vision-8b","providerModelId":"c4ai-aya-vision-8b"} } }
+    providersMapping={ {"cohere":{"modelId":"CohereLabs/aya-vision-32b","providerModelId":"c4ai-aya-vision-32b"} } }
 conversational />
 

docs/inference-providers/providers/fal-ai.md

@@ -64,6 +64,6 @@ Find out more about Text To Video [here](../tasks/text_to_video).
 
 <InferenceSnippet
     pipeline=text-to-video
-    providersMapping={ {"fal-ai":{"modelId":"Wan-AI/Wan2.1-T2V-14B","providerModelId":"fal-ai/wan-t2v"} } }
+    providersMapping={ {"fal-ai":{"modelId":"Lightricks/LTX-Video","providerModelId":"fal-ai/ltx-video"} } }
 />
 

docs/inference-providers/providers/hf-inference.md

@@ -39,13 +39,23 @@ If you are interested in deploying models to a dedicated and autoscaling infrast
 ## Supported tasks
 
 
+### Audio Classification
+
+Find out more about Audio Classification [here](../tasks/audio_classification).
+
+<InferenceSnippet
+    pipeline=audio-classification
+    providersMapping={ {"hf-inference":{"modelId":"firdhokk/speech-emotion-recognition-with-openai-whisper-large-v3","providerModelId":"firdhokk/speech-emotion-recognition-with-openai-whisper-large-v3"} } }
+/>
+
+
 ### Automatic Speech Recognition
 
 Find out more about Automatic Speech Recognition [here](../tasks/automatic_speech_recognition).
 
 <InferenceSnippet
     pipeline=automatic-speech-recognition
-    providersMapping={ {"hf-inference":{"modelId":"openai/whisper-large-v3-turbo","providerModelId":"openai/whisper-large-v3-turbo"} } }
+    providersMapping={ {"hf-inference":{"modelId":"openai/whisper-large-v3","providerModelId":"openai/whisper-large-v3"} } }
 />
 
 
@@ -65,7 +75,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"hf-inference":{"modelId":"meta-llama/Llama-3.2-11B-Vision-Instruct","providerModelId":"meta-llama/Llama-3.2-11B-Vision-Instruct"} } }
+    providersMapping={ {"hf-inference":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it"} } }
 conversational />
 
 
@@ -75,7 +85,77 @@ Find out more about Feature Extraction [here](../tasks/feature_extraction).
 
 <InferenceSnippet
     pipeline=feature-extraction
-    providersMapping={ {"hf-inference":{"modelId":"kyutai/mimi","providerModelId":"kyutai/mimi"} } }
+    providersMapping={ {"hf-inference":{"modelId":"intfloat/multilingual-e5-large-instruct","providerModelId":"intfloat/multilingual-e5-large-instruct"} } }
+/>
+
+
+### Fill Mask
+
+Find out more about Fill Mask [here](../tasks/fill_mask).
+
+<InferenceSnippet
+    pipeline=fill-mask
+    providersMapping={ {"hf-inference":{"modelId":"google-bert/bert-base-uncased","providerModelId":"google-bert/bert-base-uncased"} } }
+/>
+
+
+### Image Classification
+
+Find out more about Image Classification [here](../tasks/image_classification).
+
+<InferenceSnippet
+    pipeline=image-classification
+    providersMapping={ {"hf-inference":{"modelId":"Falconsai/nsfw_image_detection","providerModelId":"Falconsai/nsfw_image_detection"} } }
+/>
+
+
+### Image Segmentation
+
+Find out more about Image Segmentation [here](../tasks/image_segmentation).
+
+<InferenceSnippet
+    pipeline=image-segmentation
+    providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"} } }
+/>
+
+
+### Object Detection
+
+Find out more about Object Detection [here](../tasks/object_detection).
+
+<InferenceSnippet
+    pipeline=object-detection
+    providersMapping={ {"hf-inference":{"modelId":"facebook/detr-resnet-50","providerModelId":"facebook/detr-resnet-50"} } }
+/>
+
+
+### Question Answering
+
+Find out more about Question Answering [here](../tasks/question_answering).
+
+<InferenceSnippet
+    pipeline=question-answering
+    providersMapping={ {"hf-inference":{"modelId":"deepset/roberta-base-squad2","providerModelId":"deepset/roberta-base-squad2"} } }
+/>
+
+
+### Summarization
+
+Find out more about Summarization [here](../tasks/summarization).
+
+<InferenceSnippet
+    pipeline=summarization
+    providersMapping={ {"hf-inference":{"modelId":"facebook/bart-large-cnn","providerModelId":"facebook/bart-large-cnn"} } }
+/>
+
+
+### Table Question Answering
+
+Find out more about Table Question Answering [here](../tasks/table_question_answering).
+
+<InferenceSnippet
+    pipeline=table-question-answering
+    providersMapping={ {"hf-inference":{"modelId":"google/tapas-base-finetuned-wtq","providerModelId":"google/tapas-base-finetuned-wtq"} } }
 />
 
 
@@ -108,3 +188,33 @@ Find out more about Text To Image [here](../tasks/text_to_image).
     providersMapping={ {"hf-inference":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/FLUX.1-dev"} } }
 />
 
+
+### Token Classification
+
+Find out more about Token Classification [here](../tasks/token_classification).
+
+<InferenceSnippet
+    pipeline=token-classification
+    providersMapping={ {"hf-inference":{"modelId":"dslim/bert-base-NER","providerModelId":"dslim/bert-base-NER"} } }
+/>
+
+
+### Translation
+
+Find out more about Translation [here](../tasks/translation).
+
+<InferenceSnippet
+    pipeline=translation
+    providersMapping={ {"hf-inference":{"modelId":"google-t5/t5-base","providerModelId":"google-t5/t5-base"} } }
+/>
+
+
+### Zero Shot Classification
+
+Find out more about Zero Shot Classification [here](../tasks/zero_shot_classification).
+
+<InferenceSnippet
+    pipeline=zero-shot-classification
+    providersMapping={ {"hf-inference":{"modelId":"facebook/bart-large-mnli","providerModelId":"facebook/bart-large-mnli"} } }
+/>
+

docs/inference-providers/providers/nebius.md

@@ -44,7 +44,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"nebius":{"modelId":"deepseek-ai/DeepSeek-V3-0324","providerModelId":"deepseek-ai/DeepSeek-V3-0324-fast"} } }
+    providersMapping={ {"nebius":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"Qwen/Qwen3-235B-A22B"} } }
 conversational />
 
 

docs/inference-providers/register-as-a-provider.md

@@ -473,7 +473,11 @@ Here's how to add your documentation page:
 -   Submit the Documentation PR:
     *   Add your new `{provider-name}.handlebars` file.
     *   Update the [partners table](./index#partners) to include your company or product.
-
+    *   Update the `_toctree.yml` file in the `docs/inference-providers/` directory to include your new documentation page in the "Providers" section, maintaining alphabetical order.
+    *   Update the `scripts/inference-providers/scripts/generate.ts` file to include your provider in the `PROVIDERS_HUB_ORGS` and `PROVIDERS_URLS` constants, maintaining alphabetical order.
+    *   Run `pnpm install` (if you haven't already) and then `pnpm run generate` at the root of the `scripts/inference-providers` repository to generate the documentation. 
+    *    Commit all your changes, including the manually edited files (provider page, `_toctree.yml`, partners table) and the files generated by the script.
+    *   When you open the PR, please ping @Wauplin, @SBrandeis, @julien-c, and @hanouticelina for a review. If you need any assistance with these steps, please reach out – we're here to help you!
 
 ## FAQ
 

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

@@ -29,13 +29,17 @@ 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.
 
 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
 
 
-There are currently no snippet examples for the **audio-classification** task, as no providers support it yet.
+<InferenceSnippet
+    pipeline=audio-classification
+    providersMapping={ {"hf-inference":{"modelId":"firdhokk/speech-emotion-recognition-with-openai-whisper-large-v3","providerModelId":"firdhokk/speech-emotion-recognition-with-openai-whisper-large-v3"}} }
+/>
 
 
 

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

@@ -38,7 +38,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=automatic-speech-recognition
-    providersMapping={ {"fal-ai":{"modelId":"openai/whisper-large-v3","providerModelId":"fal-ai/whisper"},"hf-inference":{"modelId":"openai/whisper-large-v3-turbo","providerModelId":"openai/whisper-large-v3-turbo"}} }
+    providersMapping={ {"fal-ai":{"modelId":"openai/whisper-large-v3","providerModelId":"fal-ai/whisper"},"hf-inference":{"modelId":"openai/whisper-large-v3","providerModelId":"openai/whisper-large-v3"}} }
 />
 
 

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

@@ -24,6 +24,7 @@ This is a subtask of [`text-generation`](https://huggingface.co/docs/inference-p
 - [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it): A text-generation model trained to follow instructions.
 - [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct): Very powerful text generation model trained to follow instructions.
 - [microsoft/phi-4](https://huggingface.co/microsoft/phi-4): Powerful text generation model by Microsoft.
+- [Qwen/Qwen2.5-7B-Instruct-1M](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M): Strong conversational model that supports very long instructions.
 - [Qwen/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct): Text generation model used to write code.
 - [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1): Powerful reasoning based open large language model.
 
@@ -59,7 +60,7 @@ The API supports:
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b"},"cohere":{"modelId":"CohereLabs/c4ai-command-a-03-2025","providerModelId":"command-a-03-2025"},"fireworks-ai":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"accounts/fireworks/models/qwen3-235b-a22b"},"hf-inference":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"Qwen/Qwen3-235B-A22B"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-V3-0324","providerModelId":"deepseek-ai/DeepSeek-V3-0324"},"nebius":{"modelId":"deepseek-ai/DeepSeek-V3-0324","providerModelId":"deepseek-ai/DeepSeek-V3-0324-fast"},"novita":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"qwen/qwen3-235b-a22b-fp8"},"sambanova":{"modelId":"deepseek-ai/DeepSeek-V3-0324","providerModelId":"DeepSeek-V3-0324"},"together":{"modelId":"deepseek-ai/DeepSeek-R1","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
+    providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b"},"cohere":{"modelId":"CohereLabs/c4ai-command-a-03-2025","providerModelId":"command-a-03-2025"},"fireworks-ai":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"accounts/fireworks/models/qwen3-235b-a22b"},"hf-inference":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"Qwen/Qwen3-235B-A22B"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-V3-0324","providerModelId":"deepseek-ai/DeepSeek-V3-0324"},"nebius":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"Qwen/Qwen3-235B-A22B"},"novita":{"modelId":"Qwen/Qwen3-235B-A22B","providerModelId":"qwen/qwen3-235b-a22b-fp8"},"sambanova":{"modelId":"deepseek-ai/DeepSeek-V3-0324","providerModelId":"DeepSeek-V3-0324"},"together":{"modelId":"deepseek-ai/DeepSeek-R1","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
 conversational />
 
 
@@ -69,7 +70,7 @@ conversational />
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"},"cohere":{"modelId":"CohereLabs/aya-vision-8b","providerModelId":"c4ai-aya-vision-8b"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"hf-inference":{"modelId":"meta-llama/Llama-3.2-11B-Vision-Instruct","providerModelId":"meta-llama/Llama-3.2-11B-Vision-Instruct"},"hyperbolic":{"modelId":"Qwen/Qwen2.5-VL-7B-Instruct","providerModelId":"Qwen/Qwen2.5-VL-7B-Instruct"},"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"},"novita":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"Llama-4-Scout-17B-16E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
+    providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"},"cohere":{"modelId":"CohereLabs/aya-vision-32b","providerModelId":"c4ai-aya-vision-32b"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"hf-inference":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it"},"hyperbolic":{"modelId":"Qwen/Qwen2.5-VL-7B-Instruct","providerModelId":"Qwen/Qwen2.5-VL-7B-Instruct"},"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"},"novita":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"Llama-4-Scout-17B-16E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
 conversational />
 
 
@@ -120,6 +121,11 @@ conversational />
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(#2)** | _object_ |  |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;type*** | _enum_ | Possible values: regex. |
 | **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;value*** | _string_ |  |
+| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(#3)** | _object_ |  |
+| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;type*** | _enum_ | Possible values: json_schema. |
+| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;value*** | _object_ |  |
+| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;name** | _string_ | Optional name identifier for the schema |
+| **&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;schema*** | _unknown_ | The actual JSON schema definition |
 | **seed** | _integer_ |  |
 | **stop** | _string[]_ | Up to 4 sequences where the API will stop generating further tokens. |
 | **stream** | _boolean_ |  |

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

@@ -29,6 +29,7 @@ For more details about the `feature-extraction` task, check out its [dedicated p
 
 ### Recommended models
 
+- [thenlper/gte-large](https://huggingface.co/thenlper/gte-large): A powerful feature extraction model for natural language processing tasks.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=feature-extraction&sort=trending).
 
@@ -37,7 +38,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=feature-extraction
-    providersMapping={ {"hf-inference":{"modelId":"kyutai/mimi","providerModelId":"kyutai/mimi"},"sambanova":{"modelId":"intfloat/e5-mistral-7b-instruct","providerModelId":"E5-Mistral-7B-Instruct"}} }
+    providersMapping={ {"hf-inference":{"modelId":"intfloat/multilingual-e5-large-instruct","providerModelId":"intfloat/multilingual-e5-large-instruct"},"sambanova":{"modelId":"intfloat/e5-mistral-7b-instruct","providerModelId":"E5-Mistral-7B-Instruct"}} }
 />
 
 

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

@@ -24,13 +24,17 @@ For more details about the `fill-mask` task, check out its [dedicated page](http
 
 ### Recommended models
 
+- [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base): A multilingual model trained on 100 languages.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=fill-mask&sort=trending).
 
 ### Using the API
 
 
-There are currently no snippet examples for the **fill-mask** task, as no providers support it yet.
+<InferenceSnippet
+    pipeline=fill-mask
+    providersMapping={ {"hf-inference":{"modelId":"google-bert/bert-base-uncased","providerModelId":"google-bert/bert-base-uncased"}} }
+/>
 
 
 

docs/inference-providers/tasks/image-classification.md

@@ -24,13 +24,18 @@ For more details about the `image-classification` task, check out its [dedicated
 
 ### Recommended models
 
+- [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224): A strong image classification model.
+- [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224): A robust image classification model.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=image-classification&sort=trending).
 
 ### Using the API
 
 
-There are currently no snippet examples for the **image-classification** task, as no providers support it yet.
+<InferenceSnippet
+    pipeline=image-classification
+    providersMapping={ {"hf-inference":{"modelId":"Falconsai/nsfw_image_detection","providerModelId":"Falconsai/nsfw_image_detection"}} }
+/>
 
 
 

docs/inference-providers/tasks/image-segmentation.md

@@ -24,13 +24,17 @@ For more details about the `image-segmentation` task, check out its [dedicated p
 
 ### Recommended models
 
+- [facebook/mask2former-swin-large-coco-panoptic](https://huggingface.co/facebook/mask2former-swin-large-coco-panoptic): Panoptic segmentation model trained on the COCO (common objects) dataset.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=image-segmentation&sort=trending).
 
 ### Using the API
 
 
-There are currently no snippet examples for the **image-segmentation** task, as no providers support it yet.
+<InferenceSnippet
+    pipeline=image-segmentation
+    providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"}} }
+/>
 
 
 

docs/inference-providers/tasks/object-detection.md

@@ -24,13 +24,17 @@ For more details about the `object-detection` task, check out its [dedicated pag
 
 ### Recommended models
 
+- [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50): Solid object detection model pre-trained on the COCO 2017 dataset.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=object-detection&sort=trending).
 
 ### Using the API
 
 
-There are currently no snippet examples for the **object-detection** task, as no providers support it yet.
+<InferenceSnippet
+    pipeline=object-detection
+    providersMapping={ {"hf-inference":{"modelId":"facebook/detr-resnet-50","providerModelId":"facebook/detr-resnet-50"}} }
+/>