Update Inference Providers documentation (automated)

Wauplin · github-actions[bot] · commit 1e3babb1b38e · 2025-04-18T03:20:10.000Z
diff --git a/docs/inference-providers/providers/cerebras.md b/docs/inference-providers/providers/cerebras.md
@@ -47,3 +47,13 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
     providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b"} } }
 conversational />
 
+
+### Chat Completion (VLM)
+
+Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
+
+<InferenceSnippet
+    pipeline=image-text-to-text
+    providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"} } }
+conversational />
+
diff --git a/docs/inference-providers/providers/fal-ai.md b/docs/inference-providers/providers/fal-ai.md
@@ -54,7 +54,7 @@ Find out more about Text To Image [here](../tasks/text_to_image).
 
 <InferenceSnippet
     pipeline=text-to-image
-    providersMapping={ {"fal-ai":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"fal-ai/flux/dev"} } }
+    providersMapping={ {"fal-ai":{"modelId":"HiDream-ai/HiDream-I1-Full","providerModelId":"fal-ai/hidream-i1-full"} } }
 />
 
 
diff --git a/docs/inference-providers/providers/hf-inference.md b/docs/inference-providers/providers/hf-inference.md
@@ -39,16 +39,6 @@ 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":"ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition","providerModelId":"ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition"} } }
-/>
-
-
 ### Automatic Speech Recognition
 
 Find out more about Automatic Speech Recognition [here](../tasks/automatic_speech_recognition).
@@ -75,7 +65,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"hf-inference":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it"} } }
+    providersMapping={ {"hf-inference":{"modelId":"meta-llama/Llama-3.2-11B-Vision-Instruct","providerModelId":"meta-llama/Llama-3.2-11B-Vision-Instruct"} } }
 conversational />
 
 
@@ -85,17 +75,7 @@ Find out more about Feature Extraction [here](../tasks/feature_extraction).
 
 <InferenceSnippet
     pipeline=feature-extraction
-    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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"mixedbread-ai/mxbai-embed-large-v1","providerModelId":"mixedbread-ai/mxbai-embed-large-v1"} } }
 />
 
 
@@ -109,13 +89,13 @@ Find out more about Image Classification [here](../tasks/image_classification).
 />
 
 
-### Image To Image
+### Image Segmentation
 
-Find out more about Image To Image [here](../tasks/image_to_image).
+Find out more about Image Segmentation [here](../tasks/image_segmentation).
 
 <InferenceSnippet
-    pipeline=image-to-image
-    providersMapping={ {"hf-inference":{"modelId":"enhanceaiteam/Flux-Uncensored-V2","providerModelId":"black-forest-labs/FLUX.1-dev"} } }
+    pipeline=image-segmentation
+    providersMapping={ {"hf-inference":{"modelId":"jonathandinu/face-parsing","providerModelId":"jonathandinu/face-parsing"} } }
 />
 
 
@@ -125,7 +105,7 @@ 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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"Matthieu68857/pokemon-cards-detection","providerModelId":"Matthieu68857/pokemon-cards-detection"} } }
 />
 
 
@@ -135,7 +115,7 @@ Find out more about Question Answering [here](../tasks/question_answering).
 
 <InferenceSnippet
     pipeline=question-answering
-    providersMapping={ {"hf-inference":{"modelId":"deepset/gelectra-large-germanquad","providerModelId":"deepset/gelectra-large-germanquad"} } }
+    providersMapping={ {"hf-inference":{"modelId":"google-bert/bert-large-uncased-whole-word-masking-finetuned-squad","providerModelId":"google-bert/bert-large-uncased-whole-word-masking-finetuned-squad"} } }
 />
 
 
@@ -155,7 +135,7 @@ Find out more about Text Classification [here](../tasks/text_classification).
 
 <InferenceSnippet
     pipeline=text-classification
-    providersMapping={ {"hf-inference":{"modelId":"ProsusAI/finbert","providerModelId":"ProsusAI/finbert"} } }
+    providersMapping={ {"hf-inference":{"modelId":"distilbert/distilbert-base-uncased-finetuned-sst-2-english","providerModelId":"distilbert/distilbert-base-uncased-finetuned-sst-2-english"} } }
 />
 
 
@@ -179,23 +159,13 @@ Find out more about Text To Image [here](../tasks/text_to_image).
 />
 
 
-### Text To Video
-
-Find out more about Text To Video [here](../tasks/text_to_video).
-
-<InferenceSnippet
-    pipeline=text-to-video
-    providersMapping={ {"hf-inference":{"modelId":"AdamLucek/Wan2.1-T2V-14B-OldBookIllustrations","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":"dbmdz/bert-large-cased-finetuned-conll03-english","providerModelId":"dbmdz/bert-large-cased-finetuned-conll03-english"} } }
+    providersMapping={ {"hf-inference":{"modelId":"dslim/bert-base-NER","providerModelId":"dslim/bert-base-NER"} } }
 />
 
 
diff --git a/docs/inference-providers/providers/nebius.md b/docs/inference-providers/providers/nebius.md
@@ -54,7 +54,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"} } }
+    providersMapping={ {"nebius":{"modelId":"mistralai/Mistral-Small-3.1-24B-Instruct-2503","providerModelId":"mistralai/Mistral-Small-3.1-24B-Instruct-2503"} } }
 conversational />
 
 
diff --git a/docs/inference-providers/providers/novita.md b/docs/inference-providers/providers/novita.md
@@ -33,7 +33,9 @@ For more details, check out the `generate.ts` script: https://github.com/hugging
     </a>
 </div>
 
-​Novita AI is a comprehensive AI cloud platform that provides developers and businesses with access to over 200 APIs for tasks such as image generation, video processing, audio synthesis, and large language models.
+[Novita](https://novita.ai) is the go-to inference platform for AI developers seeking a low-cost, reliable, and simple solution for shipping AI models.
+
+Offering 200+ APIs (LLMs, image, video, audio) with fully managed deployment — enterprise-grade, scalable, and maintenance-free.
 
 ## Supported tasks
 
@@ -57,13 +59,3 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
     providersMapping={ {"novita":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"} } }
 conversational />
 
-
-### Text To Video
-
-Find out more about Text To Video [here](../tasks/text_to_video).
-
-<InferenceSnippet
-    pipeline=text-to-video
-    providersMapping={ {"novita":{"modelId":"Wan-AI/Wan2.1-T2V-14B","providerModelId":"wan-t2v"} } }
-/>
-
diff --git a/docs/inference-providers/tasks/audio-classification.md b/docs/inference-providers/tasks/audio-classification.md
@@ -29,19 +29,13 @@ 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).
 
 ### Using the API
 
 
-<InferenceSnippet
-    pipeline=audio-classification
-    providersMapping={ {"hf-inference":{"modelId":"ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition","providerModelId":"ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition"}} }
-/>
+No snippet available for this task.
 
 
 
diff --git a/docs/inference-providers/tasks/automatic-speech-recognition.md b/docs/inference-providers/tasks/automatic-speech-recognition.md
@@ -30,7 +30,6 @@ 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.
-- [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).
 
diff --git a/docs/inference-providers/tasks/feature-extraction.md b/docs/inference-providers/tasks/feature-extraction.md
@@ -29,7 +29,6 @@ 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).
 
@@ -38,7 +37,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=feature-extraction
-    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"}} }
+    providersMapping={ {"hf-inference":{"modelId":"mixedbread-ai/mxbai-embed-large-v1","providerModelId":"mixedbread-ai/mxbai-embed-large-v1"},"sambanova":{"modelId":"intfloat/e5-mistral-7b-instruct","providerModelId":"E5-Mistral-7B-Instruct"}} }
 />
 
 
diff --git a/docs/inference-providers/tasks/fill-mask.md b/docs/inference-providers/tasks/fill-mask.md
@@ -24,17 +24,13 @@ 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
 
 
-<InferenceSnippet
-    pipeline=fill-mask
-    providersMapping={ {"hf-inference":{"modelId":"google-bert/bert-base-uncased","providerModelId":"google-bert/bert-base-uncased"}} }
-/>
+No snippet available for this task.
 
 
 
diff --git a/docs/inference-providers/tasks/image-classification.md b/docs/inference-providers/tasks/image-classification.md
@@ -24,9 +24,6 @@ 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.
-- [facebook/convnext-large-224](https://huggingface.co/facebook/convnext-large-224): A strong 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).
 
diff --git a/docs/inference-providers/tasks/image-segmentation.md b/docs/inference-providers/tasks/image-segmentation.md
@@ -24,15 +24,16 @@ For more details about the `image-segmentation` task, check out its [dedicated p
 
 ### Recommended models
 
-- [openmmlab/upernet-convnext-small](https://huggingface.co/openmmlab/upernet-convnext-small): Solid semantic segmentation model trained on ADE20k.
-- [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
 
 
-No snippet available for this task.
+<InferenceSnippet
+    pipeline=image-segmentation
+    providersMapping={ {"hf-inference":{"modelId":"jonathandinu/face-parsing","providerModelId":"jonathandinu/face-parsing"}} }
+/>
 
 
 
diff --git a/docs/inference-providers/tasks/image-to-image.md b/docs/inference-providers/tasks/image-to-image.md
@@ -35,10 +35,7 @@ Explore all available models and find the one that suits you best [here](https:/
 ### Using the API
 
 
-<InferenceSnippet
-    pipeline=image-to-image
-    providersMapping={ {"hf-inference":{"modelId":"enhanceaiteam/Flux-Uncensored-V2","providerModelId":"black-forest-labs/FLUX.1-dev"}} }
-/>
+No snippet available for this task.
 
 
 
diff --git a/docs/inference-providers/tasks/object-detection.md b/docs/inference-providers/tasks/object-detection.md
@@ -24,7 +24,6 @@ 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).
 
@@ -33,7 +32,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=object-detection
-    providersMapping={ {"hf-inference":{"modelId":"facebook/detr-resnet-50","providerModelId":"facebook/detr-resnet-50"}} }
+    providersMapping={ {"hf-inference":{"modelId":"Matthieu68857/pokemon-cards-detection","providerModelId":"Matthieu68857/pokemon-cards-detection"}} }
 />
 
 
diff --git a/docs/inference-providers/tasks/question-answering.md b/docs/inference-providers/tasks/question-answering.md
@@ -24,9 +24,6 @@ For more details about the `question-answering` task, check out its [dedicated p
 
 ### Recommended models
 
-- [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2): A robust baseline model for most question answering domains.
-- [distilbert/distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-cased-distilled-squad): Small yet robust model that can answer questions.
-- [google/tapas-base-finetuned-wtq](https://huggingface.co/google/tapas-base-finetuned-wtq): A special model that can answer questions from tables.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=question-answering&sort=trending).
 
@@ -35,7 +32,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=question-answering
-    providersMapping={ {"hf-inference":{"modelId":"deepset/gelectra-large-germanquad","providerModelId":"deepset/gelectra-large-germanquad"}} }
+    providersMapping={ {"hf-inference":{"modelId":"google-bert/bert-large-uncased-whole-word-masking-finetuned-squad","providerModelId":"google-bert/bert-large-uncased-whole-word-masking-finetuned-squad"}} }
 />
 
 
diff --git a/docs/inference-providers/tasks/summarization.md b/docs/inference-providers/tasks/summarization.md
@@ -25,7 +25,6 @@ For more details about the `summarization` task, check out its [dedicated page](
 ### Recommended models
 
 - [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn): A strong summarization model trained on English news articles. Excels at generating factual summaries.
-- [Falconsai/medical_summarization](https://huggingface.co/Falconsai/medical_summarization): A summarization model trained on medical articles.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=summarization&sort=trending).
 
diff --git a/docs/inference-providers/tasks/table-question-answering.md b/docs/inference-providers/tasks/table-question-answering.md
@@ -24,8 +24,6 @@ For more details about the `table-question-answering` task, check out its [dedic
 
 ### Recommended models
 
-- [microsoft/tapex-base](https://huggingface.co/microsoft/tapex-base): A table question answering model that is capable of neural SQL execution, i.e., employ TAPEX to execute a SQL query on a given table.
-- [google/tapas-base-finetuned-wtq](https://huggingface.co/google/tapas-base-finetuned-wtq): A robust table question answering model.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=table-question-answering&sort=trending).
 
diff --git a/docs/inference-providers/tasks/text-classification.md b/docs/inference-providers/tasks/text-classification.md
@@ -25,10 +25,6 @@ For more details about the `text-classification` task, check out its [dedicated
 ### Recommended models
 
 - [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english): A robust model trained for sentiment analysis.
-- [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert): A sentiment analysis model specialized in financial sentiment.
-- [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest): A sentiment analysis model specialized in analyzing tweets.
-- [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection): A model that can classify languages.
-- [meta-llama/Prompt-Guard-86M](https://huggingface.co/meta-llama/Prompt-Guard-86M): A model that can classify text generation attacks.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=text-classification&sort=trending).
 
@@ -37,7 +33,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=text-classification
-    providersMapping={ {"hf-inference":{"modelId":"ProsusAI/finbert","providerModelId":"ProsusAI/finbert"}} }
+    providersMapping={ {"hf-inference":{"modelId":"distilbert/distilbert-base-uncased-finetuned-sst-2-english","providerModelId":"distilbert/distilbert-base-uncased-finetuned-sst-2-english"}} }
 />
 
 
diff --git a/docs/inference-providers/tasks/text-generation.md b/docs/inference-providers/tasks/text-generation.md
@@ -27,7 +27,6 @@ For more details about the `text-generation` task, check out its [dedicated page
 ### Recommended models
 
 - [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it): A text-generation model trained to follow instructions.
-- [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B): Smaller variant of one of the most powerful models.
 - [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-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct): Text generation model used to write code.
diff --git a/docs/inference-providers/tasks/text-to-image.md b/docs/inference-providers/tasks/text-to-image.md
@@ -35,7 +35,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=text-to-image
-    providersMapping={ {"fal-ai":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"fal-ai/flux/dev"},"hf-inference":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/FLUX.1-dev"},"nebius":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/flux-dev"},"replicate":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/flux-dev"},"together":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/FLUX.1-dev"}} }
+    providersMapping={ {"fal-ai":{"modelId":"HiDream-ai/HiDream-I1-Full","providerModelId":"fal-ai/hidream-i1-full"},"hf-inference":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/FLUX.1-dev"},"nebius":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/flux-dev"},"replicate":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/flux-dev"},"together":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/FLUX.1-dev"}} }
 />
 
 
diff --git a/docs/inference-providers/tasks/text-to-video.md b/docs/inference-providers/tasks/text-to-video.md
diff --git a/docs/inference-providers/tasks/token-classification.md b/docs/inference-providers/tasks/token-classification.md
diff --git a/docs/inference-providers/tasks/translation.md b/docs/inference-providers/tasks/translation.md
diff --git a/scripts/inference-providers/package.json b/scripts/inference-providers/package.json
diff --git a/scripts/inference-providers/pnpm-lock.yaml b/scripts/inference-providers/pnpm-lock.yaml
