huggingface · Wauplin · Jul 4, 2025 · Jul 4, 2025
diff --git a/docs/inference-providers/providers/featherless-ai.md b/docs/inference-providers/providers/featherless-ai.md
@@ -52,7 +52,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"} } }
+    providersMapping={ {"featherless-ai":{"modelId":"mistralai/Magistral-Small-2506","providerModelId":"mistralai/Magistral-Small-2506"} } }
 conversational />
 
 
@@ -62,7 +62,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"featherless-ai":{"modelId":"google/medgemma-4b-it","providerModelId":"google/medgemma-4b-it"} } }
+    providersMapping={ {"featherless-ai":{"modelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it","providerModelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it"} } }
 conversational />
 
 
@@ -72,6 +72,6 @@ Find out more about Text Generation [here](../tasks/text_generation).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"} } }
+    providersMapping={ {"featherless-ai":{"modelId":"mistralai/Magistral-Small-2506","providerModelId":"mistralai/Magistral-Small-2506"} } }
 />
 
diff --git a/docs/inference-providers/providers/hf-inference.md b/docs/inference-providers/providers/hf-inference.md
@@ -45,26 +45,6 @@ If you are interested in deploying models to a dedicated and autoscaling infrast
 ## Supported tasks
 
 
-### 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","providerModelId":"openai/whisper-large-v3"} } }
-/>
-
-
-### Chat Completion (VLM)
-
-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"} } }
-conversational />
-
-
 ### Feature Extraction
 
 Find out more about Feature Extraction [here](../tasks/feature_extraction).
@@ -91,7 +71,7 @@ Find out more about Image Classification [here](../tasks/image_classification).
 
 <InferenceSnippet
     pipeline=image-classification
-    providersMapping={ {"hf-inference":{"modelId":"dima806/fairface_age_image_detection","providerModelId":"dima806/fairface_age_image_detection"} } }
+    providersMapping={ {"hf-inference":{"modelId":"Falconsai/nsfw_image_detection","providerModelId":"Falconsai/nsfw_image_detection"} } }
 />
 
 
@@ -101,17 +81,7 @@ Find out more about Image Segmentation [here](../tasks/image_segmentation).
 
 <InferenceSnippet
     pipeline=image-segmentation
-    providersMapping={ {"hf-inference":{"modelId":"nvidia/segformer-b0-finetuned-ade-512-512","providerModelId":"nvidia/segformer-b0-finetuned-ade-512-512"} } }
-/>
-
-
-### 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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"} } }
 />
 
 
@@ -121,7 +91,7 @@ Find out more about Question Answering [here](../tasks/question_answering).
 
 <InferenceSnippet
     pipeline=question-answering
-    providersMapping={ {"hf-inference":{"modelId":"uer/roberta-base-chinese-extractive-qa","providerModelId":"uer/roberta-base-chinese-extractive-qa"} } }
+    providersMapping={ {"hf-inference":{"modelId":"deepset/roberta-base-squad2","providerModelId":"deepset/roberta-base-squad2"} } }
 />
 
 
@@ -141,7 +111,7 @@ Find out more about Table Question Answering [here](../tasks/table_question_answ
 
 <InferenceSnippet
     pipeline=table-question-answering
-    providersMapping={ {"hf-inference":{"modelId":"google/tapas-large-finetuned-wtq","providerModelId":"google/tapas-large-finetuned-wtq"} } }
+    providersMapping={ {"hf-inference":{"modelId":"google/tapas-base-finetuned-wtq","providerModelId":"google/tapas-base-finetuned-wtq"} } }
 />
 
 
@@ -155,23 +125,13 @@ Find out more about Text Classification [here](../tasks/text_classification).
 />
 
 
-### Text To Image
-
-Find out more about Text To Image [here](../tasks/text_to_image).
-
-<InferenceSnippet
-    pipeline=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":"DeepMount00/Italian_NER_XXL","providerModelId":"DeepMount00/Italian_NER_XXL"} } }
+    providersMapping={ {"hf-inference":{"modelId":"dslim/bert-base-NER","providerModelId":"dslim/bert-base-NER"} } }
 />
 
 
@@ -181,6 +141,6 @@ Find out more about Translation [here](../tasks/translation).
 
 <InferenceSnippet
     pipeline=translation
-    providersMapping={ {"hf-inference":{"modelId":"Helsinki-NLP/opus-mt-zh-en","providerModelId":"Helsinki-NLP/opus-mt-zh-en"} } }
+    providersMapping={ {"hf-inference":{"modelId":"google-t5/t5-base","providerModelId":"google-t5/t5-base"} } }
 />
 
diff --git a/docs/inference-providers/tasks/automatic-speech-recognition.md b/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","providerModelId":"openai/whisper-large-v3"}} }
+    providersMapping={ {"fal-ai":{"modelId":"openai/whisper-large-v3","providerModelId":"fal-ai/whisper"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/chat-completion.md b/docs/inference-providers/tasks/chat-completion.md
@@ -63,7 +63,7 @@ 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-r-plus","providerModelId":"command-r-plus-04-2024"},"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"fireworks-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"accounts/fireworks/models/deepseek-r1-0528"},"groq":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b-versatile"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"nebius":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"novita":{"modelId":"MiniMaxAI/MiniMax-M1-80k","providerModelId":"minimaxai/minimax-m1-80k"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"sambanova":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"DeepSeek-R1-0528"},"together":{"modelId":"deepseek-ai/DeepSeek-R1-0528","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-r-plus","providerModelId":"command-r-plus-04-2024"},"featherless-ai":{"modelId":"mistralai/Magistral-Small-2506","providerModelId":"mistralai/Magistral-Small-2506"},"fireworks-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"accounts/fireworks/models/deepseek-r1-0528"},"groq":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b-versatile"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"nebius":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"novita":{"modelId":"MiniMaxAI/MiniMax-M1-80k","providerModelId":"minimaxai/minimax-m1-80k"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"sambanova":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"DeepSeek-R1-0528"},"together":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
 conversational />
 
 
@@ -73,7 +73,7 @@ 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"},"featherless-ai":{"modelId":"google/medgemma-4b-it","providerModelId":"google/medgemma-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"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":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-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-8b","providerModelId":"c4ai-aya-vision-8b"},"featherless-ai":{"modelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it","providerModelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-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":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
 conversational />
 
 

diff --git a/docs/inference-providers/tasks/feature-extraction.md b/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).
 

diff --git a/docs/inference-providers/tasks/image-classification.md b/docs/inference-providers/tasks/image-classification.md
@@ -25,6 +25,7 @@ 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).
@@ -34,7 +35,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=image-classification
-    providersMapping={ {"hf-inference":{"modelId":"dima806/fairface_age_image_detection","providerModelId":"dima806/fairface_age_image_detection"}} }
+    providersMapping={ {"hf-inference":{"modelId":"Falconsai/nsfw_image_detection","providerModelId":"Falconsai/nsfw_image_detection"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/image-segmentation.md b/docs/inference-providers/tasks/image-segmentation.md
@@ -24,6 +24,7 @@ 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.
 
 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).
 
@@ -32,7 +33,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=image-segmentation
-    providersMapping={ {"hf-inference":{"modelId":"nvidia/segformer-b0-finetuned-ade-512-512","providerModelId":"nvidia/segformer-b0-finetuned-ade-512-512"}} }
+    providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/image-text-to-text.md b/docs/inference-providers/tasks/image-text-to-text.md
@@ -33,7 +33,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <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"},"featherless-ai":{"modelId":"google/medgemma-4b-it","providerModelId":"google/medgemma-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"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":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-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-8b","providerModelId":"c4ai-aya-vision-8b"},"featherless-ai":{"modelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it","providerModelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-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":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
 conversational />
 
 

diff --git a/docs/inference-providers/tasks/object-detection.md b/docs/inference-providers/tasks/object-detection.md
@@ -24,17 +24,13 @@ 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
 
 
-<InferenceSnippet
-    pipeline=object-detection
-    providersMapping={ {"hf-inference":{"modelId":"facebook/detr-resnet-50","providerModelId":"facebook/detr-resnet-50"}} }
-/>
+There are currently no snippet examples for the **object-detection** task, as no providers support it yet.
 
 
 

diff --git a/docs/inference-providers/tasks/question-answering.md b/docs/inference-providers/tasks/question-answering.md
@@ -24,6 +24,9 @@ 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).
 
@@ -32,7 +35,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=question-answering
-    providersMapping={ {"hf-inference":{"modelId":"uer/roberta-base-chinese-extractive-qa","providerModelId":"uer/roberta-base-chinese-extractive-qa"}} }
+    providersMapping={ {"hf-inference":{"modelId":"deepset/roberta-base-squad2","providerModelId":"deepset/roberta-base-squad2"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/table-question-answering.md b/docs/inference-providers/tasks/table-question-answering.md
@@ -24,6 +24,7 @@ For more details about the `table-question-answering` task, check out its [dedic
 
 ### Recommended models
 
+- [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).
 
@@ -32,7 +33,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=table-question-answering
-    providersMapping={ {"hf-inference":{"modelId":"google/tapas-large-finetuned-wtq","providerModelId":"google/tapas-large-finetuned-wtq"}} }
+    providersMapping={ {"hf-inference":{"modelId":"google/tapas-base-finetuned-wtq","providerModelId":"google/tapas-base-finetuned-wtq"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/text-classification.md b/docs/inference-providers/tasks/text-classification.md
@@ -24,6 +24,8 @@ 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.
 
 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).
Original file line number	Diff line number	Diff line change
Expand Up		@@ -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).

Expand Down