huggingface · Wauplin · Jul 3, 2025 · Jul 3, 2025
diff --git a/docs/inference-providers/providers/hf-inference.md b/docs/inference-providers/providers/hf-inference.md
@@ -55,16 +55,6 @@ Find out more about Automatic Speech Recognition [here](../tasks/automatic_speec
 />
 
 
-### Chat Completion (LLM)
-
-Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
-
-<InferenceSnippet
-    pipeline=text-generation
-    providersMapping={ {"hf-inference":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"} } }
-conversational />
-
-
 ### Chat Completion (VLM)
 
 Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
@@ -101,7 +91,7 @@ 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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"dima806/fairface_age_image_detection","providerModelId":"dima806/fairface_age_image_detection"} } }
 />
 
 
@@ -111,7 +101,7 @@ 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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"nvidia/segformer-b0-finetuned-ade-512-512","providerModelId":"nvidia/segformer-b0-finetuned-ade-512-512"} } }
 />
 
 
@@ -131,7 +121,7 @@ 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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"uer/roberta-base-chinese-extractive-qa","providerModelId":"uer/roberta-base-chinese-extractive-qa"} } }
 />
 
 
@@ -141,7 +131,7 @@ Find out more about Summarization [here](../tasks/summarization).
 
 <InferenceSnippet
     pipeline=summarization
-    providersMapping={ {"hf-inference":{"modelId":"Falconsai/text_summarization","providerModelId":"Falconsai/text_summarization"} } }
+    providersMapping={ {"hf-inference":{"modelId":"facebook/bart-large-cnn","providerModelId":"facebook/bart-large-cnn"} } }
 />
 
 
@@ -151,7 +141,7 @@ Find out more about Table Question Answering [here](../tasks/table_question_answ
 
 <InferenceSnippet
     pipeline=table-question-answering
-    providersMapping={ {"hf-inference":{"modelId":"google/tapas-base-finetuned-wtq","providerModelId":"google/tapas-base-finetuned-wtq"} } }
+    providersMapping={ {"hf-inference":{"modelId":"google/tapas-large-finetuned-wtq","providerModelId":"google/tapas-large-finetuned-wtq"} } }
 />
 
 
@@ -165,16 +155,6 @@ Find out more about Text Classification [here](../tasks/text_classification).
 />
 
 
-### Text Generation
-
-Find out more about Text Generation [here](../tasks/text_generation).
-
-<InferenceSnippet
-    pipeline=text-generation
-    providersMapping={ {"hf-inference":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"} } }
-/>
-
-
 ### Text To Image
 
 Find out more about Text To Image [here](../tasks/text_to_image).
@@ -191,7 +171,7 @@ 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"} } }
+    providersMapping={ {"hf-inference":{"modelId":"DeepMount00/Italian_NER_XXL","providerModelId":"DeepMount00/Italian_NER_XXL"} } }
 />
 
 
@@ -201,6 +181,6 @@ Find out more about Translation [here](../tasks/translation).
 
 <InferenceSnippet
     pipeline=translation
-    providersMapping={ {"hf-inference":{"modelId":"google-t5/t5-base","providerModelId":"google-t5/t5-base"} } }
+    providersMapping={ {"hf-inference":{"modelId":"Helsinki-NLP/opus-mt-zh-en","providerModelId":"Helsinki-NLP/opus-mt-zh-en"} } }
 />
 
diff --git a/docs/inference-providers/providers/novita.md b/docs/inference-providers/providers/novita.md
@@ -62,7 +62,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"novita":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"} } }
+    providersMapping={ {"novita":{"modelId":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"} } }
 conversational />
 
 

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"},"hf-inference":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"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":"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"}} }
 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":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"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":"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"}} }
 conversational />
 
 

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).
 

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

diff --git a/docs/inference-providers/tasks/image-segmentation.md b/docs/inference-providers/tasks/image-segmentation.md
@@ -24,8 +24,6 @@ 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).
 
@@ -34,7 +32,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=image-segmentation
-    providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"}} }
+    providersMapping={ {"hf-inference":{"modelId":"nvidia/segformer-b0-finetuned-ade-512-512","providerModelId":"nvidia/segformer-b0-finetuned-ade-512-512"}} }
 />
 
 

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":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"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":"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"}} }
 conversational />
 
 

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/roberta-base-squad2","providerModelId":"deepset/roberta-base-squad2"}} }
+    providersMapping={ {"hf-inference":{"modelId":"uer/roberta-base-chinese-extractive-qa","providerModelId":"uer/roberta-base-chinese-extractive-qa"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/summarization.md b/docs/inference-providers/tasks/summarization.md
@@ -24,6 +24,7 @@ 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).
@@ -33,7 +34,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=summarization
-    providersMapping={ {"hf-inference":{"modelId":"Falconsai/text_summarization","providerModelId":"Falconsai/text_summarization"}} }
+    providersMapping={ {"hf-inference":{"modelId":"facebook/bart-large-cnn","providerModelId":"facebook/bart-large-cnn"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/table-question-answering.md b/docs/inference-providers/tasks/table-question-answering.md
@@ -24,7 +24,6 @@ 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).
 
@@ -33,7 +32,7 @@ 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-base-finetuned-wtq","providerModelId":"google/tapas-base-finetuned-wtq"}} }
+    providersMapping={ {"hf-inference":{"modelId":"google/tapas-large-finetuned-wtq","providerModelId":"google/tapas-large-finetuned-wtq"}} }
 />
 
 

diff --git a/docs/inference-providers/tasks/text-classification.md b/docs/inference-providers/tasks/text-classification.md
@@ -24,8 +24,6 @@ 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.
 
 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).
 

diff --git a/docs/inference-providers/tasks/text-generation.md b/docs/inference-providers/tasks/text-generation.md
@@ -41,7 +41,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"hf-inference":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"together":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
+    providersMapping={ {"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"together":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
 />
Original file line number	Diff line number	Diff line change
Expand Up		@@ -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).

Expand Down