Update Inference Providers documentation (automated) (#2251)

HuggingFaceInfra · Wauplin · web-flow · commit 450b139583b2 · 2026-02-26T09:02:17.000+01:00
Co-authored-by: Wauplin &lt;11801849+Wauplin@users.noreply.github.com&gt;
diff --git a/docs/inference-providers/providers/fireworks-ai.md b/docs/inference-providers/providers/fireworks-ai.md
@@ -46,7 +46,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"fireworks-ai":{"modelId":"openai/gpt-oss-20b","providerModelId":"accounts/fireworks/models/gpt-oss-20b"} } }
+    providersMapping={ {"fireworks-ai":{"modelId":"zai-org/GLM-5","providerModelId":"accounts/fireworks/models/glm-5"} } }
 conversational />
 
 
@@ -56,6 +56,6 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"fireworks-ai":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"accounts/fireworks/models/kimi-k2p5"} } }
+    providersMapping={ {"fireworks-ai":{"modelId":"Qwen/Qwen2.5-VL-32B-Instruct","providerModelId":"accounts/fireworks/models/qwen2p5-vl-32b-instruct"} } }
 conversational />
 
diff --git a/docs/inference-providers/providers/hf-inference.md b/docs/inference-providers/providers/hf-inference.md
@@ -60,7 +60,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"hf-inference":{"modelId":"HuggingFaceTB/SmolLM3-3B","providerModelId":"HuggingFaceTB/SmolLM3-3B"} } }
+    providersMapping={ {"hf-inference":{"modelId":"katanemo/Arch-Router-1.5B","providerModelId":"katanemo/Arch-Router-1.5B"} } }
 conversational />
 
 
@@ -130,7 +130,7 @@ 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"} } }
 />
 
 
@@ -160,7 +160,7 @@ Find out more about Text Generation [here](../tasks/text-generation).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"hf-inference":{"modelId":"HuggingFaceTB/SmolLM3-3B","providerModelId":"HuggingFaceTB/SmolLM3-3B"} } }
+    providersMapping={ {"hf-inference":{"modelId":"katanemo/Arch-Router-1.5B","providerModelId":"katanemo/Arch-Router-1.5B"} } }
 />
 
 
@@ -190,7 +190,7 @@ Find out more about Translation [here](../tasks/translation).
 
 <InferenceSnippet
     pipeline=translation
-    providersMapping={ {"hf-inference":{"modelId":"google/madlad400-3b-mt","providerModelId":"google/madlad400-3b-mt"} } }
+    providersMapping={ {"hf-inference":{"modelId":"Helsinki-NLP/opus-mt-tr-en","providerModelId":"Helsinki-NLP/opus-mt-tr-en"} } }
 />
 
 
diff --git a/docs/inference-providers/providers/zai-org.md b/docs/inference-providers/providers/zai-org.md
@@ -66,7 +66,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"zai-org":{"modelId":"zai-org/GLM-4.6V","providerModelId":"glm-4.6v"} } }
+    providersMapping={ {"zai-org":{"modelId":"zai-org/GLM-4.6V-Flash","providerModelId":"glm-4.6v-flash"} } }
 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-3.1-8B-Instruct","providerModelId":"llama3.1-8b"},"cohere":{"modelId":"CohereLabs/command-a-reasoning-08-2025","providerModelId":"command-a-reasoning-08-2025"},"featherless-ai":{"modelId":"Nanbeige/Nanbeige4.1-3B","providerModelId":"Nanbeige/Nanbeige4.1-3B"},"fireworks-ai":{"modelId":"openai/gpt-oss-20b","providerModelId":"accounts/fireworks/models/gpt-oss-20b"},"groq":{"modelId":"openai/gpt-oss-20b","providerModelId":"openai/gpt-oss-20b"},"hf-inference":{"modelId":"HuggingFaceTB/SmolLM3-3B","providerModelId":"HuggingFaceTB/SmolLM3-3B"},"hyperbolic":{"modelId":"openai/gpt-oss-20b","providerModelId":"openai/gpt-oss-20b"},"novita":{"modelId":"zai-org/GLM-5","providerModelId":"zai-org/glm-5"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"ovhcloud":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"Llama-3.1-8B-Instruct"},"publicai":{"modelId":"allenai/Olmo-3.1-32B-Instruct","providerModelId":"allenai/Olmo-3.1-32B-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"Meta-Llama-3.1-8B-Instruct"},"scaleway":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"llama-3.1-8b-instruct"},"together":{"modelId":"zai-org/GLM-5","providerModelId":"zai-org/GLM-5"},"zai-org":{"modelId":"zai-org/GLM-5","providerModelId":"glm-5"}} }
+    providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"llama3.1-8b"},"cohere":{"modelId":"CohereLabs/command-a-reasoning-08-2025","providerModelId":"command-a-reasoning-08-2025"},"featherless-ai":{"modelId":"Nanbeige/Nanbeige4.1-3B","providerModelId":"Nanbeige/Nanbeige4.1-3B"},"fireworks-ai":{"modelId":"zai-org/GLM-5","providerModelId":"accounts/fireworks/models/glm-5"},"groq":{"modelId":"openai/gpt-oss-20b","providerModelId":"openai/gpt-oss-20b"},"hf-inference":{"modelId":"katanemo/Arch-Router-1.5B","providerModelId":"katanemo/Arch-Router-1.5B"},"hyperbolic":{"modelId":"openai/gpt-oss-20b","providerModelId":"openai/gpt-oss-20b"},"novita":{"modelId":"zai-org/GLM-5","providerModelId":"zai-org/glm-5"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"ovhcloud":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"Llama-3.1-8B-Instruct"},"publicai":{"modelId":"allenai/Olmo-3.1-32B-Instruct","providerModelId":"allenai/Olmo-3.1-32B-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"Meta-Llama-3.1-8B-Instruct"},"scaleway":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"llama-3.1-8b-instruct"},"together":{"modelId":"zai-org/GLM-5","providerModelId":"zai-org/GLM-5"},"zai-org":{"modelId":"zai-org/GLM-5","providerModelId":"glm-5"}} }
 conversational />
 
 
@@ -73,7 +73,7 @@ conversational />
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"cohere":{"modelId":"CohereLabs/aya-vision-32b","providerModelId":"c4ai-aya-vision-32b"},"featherless-ai":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"Qwen/Qwen3.5-397B-A17B"},"fireworks-ai":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"accounts/fireworks/models/kimi-k2p5"},"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"},"novita":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/kimi-k2.5"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"ovhcloud":{"modelId":"Qwen/Qwen2.5-VL-72B-Instruct","providerModelId":"Qwen2.5-VL-72B-Instruct"},"publicai":{"modelId":"allenai/Molmo2-8B","providerModelId":"allenai/Molmo2-8B"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"scaleway":{"modelId":"google/gemma-3-27b-it","providerModelId":"gemma-3-27b-it"},"together":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/Kimi-K2.5"},"zai-org":{"modelId":"zai-org/GLM-4.6V","providerModelId":"glm-4.6v"}} }
+    providersMapping={ {"cohere":{"modelId":"CohereLabs/aya-vision-32b","providerModelId":"c4ai-aya-vision-32b"},"featherless-ai":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"Qwen/Qwen3.5-397B-A17B"},"fireworks-ai":{"modelId":"Qwen/Qwen2.5-VL-32B-Instruct","providerModelId":"accounts/fireworks/models/qwen2p5-vl-32b-instruct"},"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"},"novita":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/kimi-k2.5"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"ovhcloud":{"modelId":"Qwen/Qwen2.5-VL-72B-Instruct","providerModelId":"Qwen2.5-VL-72B-Instruct"},"publicai":{"modelId":"allenai/Molmo2-8B","providerModelId":"allenai/Molmo2-8B"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"scaleway":{"modelId":"google/gemma-3-27b-it","providerModelId":"gemma-3-27b-it"},"together":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/Kimi-K2.5"},"zai-org":{"modelId":"zai-org/GLM-4.6V-Flash","providerModelId":"glm-4.6v-flash"}} }
 conversational />
 
 
diff --git a/docs/inference-providers/tasks/image-segmentation.md b/docs/inference-providers/tasks/image-segmentation.md
@@ -22,6 +22,7 @@ Image Segmentation divides an image into segments where each pixel in the image
 
 ### 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).
 
diff --git a/docs/inference-providers/tasks/image-text-to-text.md b/docs/inference-providers/tasks/image-text-to-text.md
@@ -31,7 +31,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"cohere":{"modelId":"CohereLabs/aya-vision-32b","providerModelId":"c4ai-aya-vision-32b"},"featherless-ai":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"Qwen/Qwen3.5-397B-A17B"},"fireworks-ai":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"accounts/fireworks/models/kimi-k2p5"},"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"},"novita":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/kimi-k2.5"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"ovhcloud":{"modelId":"Qwen/Qwen2.5-VL-72B-Instruct","providerModelId":"Qwen2.5-VL-72B-Instruct"},"publicai":{"modelId":"allenai/Molmo2-8B","providerModelId":"allenai/Molmo2-8B"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"scaleway":{"modelId":"google/gemma-3-27b-it","providerModelId":"gemma-3-27b-it"},"together":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/Kimi-K2.5"},"zai-org":{"modelId":"zai-org/GLM-4.6V","providerModelId":"glm-4.6v"}} }
+    providersMapping={ {"cohere":{"modelId":"CohereLabs/aya-vision-32b","providerModelId":"c4ai-aya-vision-32b"},"featherless-ai":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"Qwen/Qwen3.5-397B-A17B"},"fireworks-ai":{"modelId":"Qwen/Qwen2.5-VL-32B-Instruct","providerModelId":"accounts/fireworks/models/qwen2p5-vl-32b-instruct"},"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"},"novita":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/kimi-k2.5"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"ovhcloud":{"modelId":"Qwen/Qwen2.5-VL-72B-Instruct","providerModelId":"Qwen2.5-VL-72B-Instruct"},"publicai":{"modelId":"allenai/Molmo2-8B","providerModelId":"allenai/Molmo2-8B"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"scaleway":{"modelId":"google/gemma-3-27b-it","providerModelId":"gemma-3-27b-it"},"together":{"modelId":"moonshotai/Kimi-K2.5","providerModelId":"moonshotai/Kimi-K2.5"},"zai-org":{"modelId":"zai-org/GLM-4.6V-Flash","providerModelId":"glm-4.6v-flash"}} }
 conversational />
 
 
diff --git a/docs/inference-providers/tasks/summarization.md b/docs/inference-providers/tasks/summarization.md
@@ -22,6 +22,7 @@ Summarization is the task of producing a shorter version of a document while pre
 
 ### 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).
@@ -31,7 +32,7 @@ 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/text-generation.md b/docs/inference-providers/tasks/text-generation.md
@@ -39,7 +39,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"featherless-ai":{"modelId":"Nanbeige/Nanbeige4.1-3B","providerModelId":"Nanbeige/Nanbeige4.1-3B"},"hf-inference":{"modelId":"HuggingFaceTB/SmolLM3-3B","providerModelId":"HuggingFaceTB/SmolLM3-3B"}} }
+    providersMapping={ {"featherless-ai":{"modelId":"Nanbeige/Nanbeige4.1-3B","providerModelId":"Nanbeige/Nanbeige4.1-3B"},"hf-inference":{"modelId":"katanemo/Arch-Router-1.5B","providerModelId":"katanemo/Arch-Router-1.5B"}} }
 />
 
 
diff --git a/docs/inference-providers/tasks/token-classification.md b/docs/inference-providers/tasks/token-classification.md
@@ -23,6 +23,7 @@ Token classification is a task in which a label is assigned to some tokens in a
 ### Recommended models
 
 - [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER): A robust performance model to identify people, locations, organizations and names of miscellaneous entities.
+- [FacebookAI/xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-english): A strong model to identify people, locations, organizations and names in multiple languages.
 - [blaze999/Medical-NER](https://huggingface.co/blaze999/Medical-NER): A token classification model specialized on medical entity recognition.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=token-classification&sort=trending).
diff --git a/docs/inference-providers/tasks/translation.md b/docs/inference-providers/tasks/translation.md
@@ -31,7 +31,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=translation
-    providersMapping={ {"hf-inference":{"modelId":"google/madlad400-3b-mt","providerModelId":"google/madlad400-3b-mt"}} }
+    providersMapping={ {"hf-inference":{"modelId":"Helsinki-NLP/opus-mt-tr-en","providerModelId":"Helsinki-NLP/opus-mt-tr-en"}} }
 />
 
 
diff --git a/scripts/inference-providers/package.json b/scripts/inference-providers/package.json
@@ -15,7 +15,7 @@
   "license": "ISC",
   "dependencies": {
     "@huggingface/inference": "^4.13.13",
-    "@huggingface/tasks": "^0.19.86",
+    "@huggingface/tasks": "^0.19.88",
     "@types/node": "^22.5.0",
     "handlebars": "^4.7.8",
     "node": "^20.17.0",
diff --git a/scripts/inference-providers/pnpm-lock.yaml b/scripts/inference-providers/pnpm-lock.yaml

Original file line number	Diff line number	Diff line change
`@@ -22,6 +22,7 @@ Image Segmentation divides an image into segments where each pixel in the image`
`22`	`22`
`23`	`23`	`### Recommended models`
`24`	`24`
	`25`	`+- [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.`
`25`	`26`
`26`	`27`	`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).`
`27`	`28`