Update Inference Providers documentation (automated) (#2418)

Co-authored-by: Wauplin <11801849+Wauplin@users.noreply.github.com>

Author: HuggingFaceInfra

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

@@ -59,7 +59,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"featherless-ai":{"modelId":"Qwen/Qwen3.5-27B","providerModelId":"Qwen/Qwen3.5-27B"} } }
+    providersMapping={ {"featherless-ai":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"Qwen/Qwen3.5-397B-A17B"} } }
 conversational />
 
 

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

@@ -200,6 +200,6 @@ Find out more about Zero Shot Classification [here](../tasks/zero-shot-classific
 
 <InferenceSnippet
     pipeline=zero-shot-classification
-    providersMapping={ {"hf-inference":{"modelId":"MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7","providerModelId":"MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7"} } }
+    providersMapping={ {"hf-inference":{"modelId":"facebook/bart-large-mnli","providerModelId":"facebook/bart-large-mnli"} } }
 />
 

docs/inference-providers/providers/hyperbolic.md

@@ -85,7 +85,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-R1","providerModelId":"deepseek-ai/DeepSeek-R1"} } }
+    providersMapping={ {"hyperbolic":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"meta-llama/Llama-3.3-70B-Instruct"} } }
 conversational />
 
 

docs/inference-providers/providers/novita.md

@@ -49,7 +49,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"novita":{"modelId":"MiniMaxAI/MiniMax-M2.7","providerModelId":"minimax/minimax-m2.7"} } }
+    providersMapping={ {"novita":{"modelId":"zai-org/GLM-5","providerModelId":"zai-org/glm-5"} } }
 conversational />
 
 

docs/inference-providers/providers/sambanova.md

@@ -51,3 +51,13 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
     providersMapping={ {"sambanova":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"Meta-Llama-3.1-8B-Instruct"} } }
 conversational />
 
+
+### Chat Completion (VLM)
+
+Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
+
+<InferenceSnippet
+    pipeline=image-text-to-text
+    providersMapping={ {"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"} } }
+conversational />
+

docs/inference-providers/providers/together.md

@@ -47,7 +47,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=text-generation
-    providersMapping={ {"together":{"modelId":"MiniMaxAI/MiniMax-M2.7","providerModelId":"MiniMaxAI/MiniMax-M2.7"} } }
+    providersMapping={ {"together":{"modelId":"openai/gpt-oss-120b","providerModelId":"openai/gpt-oss-120b"} } }
 conversational />
 
 
@@ -57,7 +57,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
 
 <InferenceSnippet
     pipeline=image-text-to-text
-    providersMapping={ {"together":{"modelId":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31B-it"} } }
+    providersMapping={ {"together":{"modelId":"Qwen/Qwen3.5-9B","providerModelId":"Qwen/Qwen3.5-9B"} } }
 conversational />
 
 

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/tiny-aya-global","providerModelId":"tiny-aya-global"},"featherless-ai":{"modelId":"arcee-ai/Trinity-Large-Thinking","providerModelId":"arcee-ai/Trinity-Large-Thinking"},"fireworks-ai":{"modelId":"MiniMaxAI/MiniMax-M2.7","providerModelId":"accounts/fireworks/models/minimax-m2p7"},"groq":{"modelId":"openai/gpt-oss-120b","providerModelId":"openai/gpt-oss-120b"},"hf-inference":{"modelId":"katanemo/Arch-Router-1.5B","providerModelId":"katanemo/Arch-Router-1.5B"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-R1","providerModelId":"deepseek-ai/DeepSeek-R1"},"novita":{"modelId":"MiniMaxAI/MiniMax-M2.7","providerModelId":"minimax/minimax-m2.7"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"ovhcloud":{"modelId":"openai/gpt-oss-120b","providerModelId":"gpt-oss-120b"},"publicai":{"modelId":"allenai/Olmo-3-7B-Instruct","providerModelId":"allenai/Olmo-3-7B-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":"MiniMaxAI/MiniMax-M2.7","providerModelId":"MiniMaxAI/MiniMax-M2.7"},"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/tiny-aya-global","providerModelId":"tiny-aya-global"},"featherless-ai":{"modelId":"arcee-ai/Trinity-Large-Thinking","providerModelId":"arcee-ai/Trinity-Large-Thinking"},"fireworks-ai":{"modelId":"MiniMaxAI/MiniMax-M2.7","providerModelId":"accounts/fireworks/models/minimax-m2p7"},"groq":{"modelId":"openai/gpt-oss-120b","providerModelId":"openai/gpt-oss-120b"},"hf-inference":{"modelId":"katanemo/Arch-Router-1.5B","providerModelId":"katanemo/Arch-Router-1.5B"},"hyperbolic":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"meta-llama/Llama-3.3-70B-Instruct"},"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":"openai/gpt-oss-120b","providerModelId":"gpt-oss-120b"},"publicai":{"modelId":"allenai/Olmo-3-7B-Instruct","providerModelId":"allenai/Olmo-3-7B-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":"openai/gpt-oss-120b","providerModelId":"openai/gpt-oss-120b"},"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/Qwen3.5-27B","providerModelId":"Qwen/Qwen3.5-27B"},"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":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31b-it"},"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"},"scaleway":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"qwen3.5-397b-a17b"},"together":{"modelId":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31B-it"},"zai-org":{"modelId":"zai-org/GLM-4.5V","providerModelId":"glm-4.5v"}} }
+    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":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31b-it"},"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"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"scaleway":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"qwen3.5-397b-a17b"},"together":{"modelId":"Qwen/Qwen3.5-9B","providerModelId":"Qwen/Qwen3.5-9B"},"zai-org":{"modelId":"zai-org/GLM-4.5V","providerModelId":"glm-4.5v"}} }
 conversational />
 
 

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/Qwen3.5-27B","providerModelId":"Qwen/Qwen3.5-27B"},"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":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31b-it"},"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"},"scaleway":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"qwen3.5-397b-a17b"},"together":{"modelId":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31B-it"},"zai-org":{"modelId":"zai-org/GLM-4.5V","providerModelId":"glm-4.5v"}} }
+    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":"google/gemma-4-31B-it","providerModelId":"google/gemma-4-31b-it"},"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"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"scaleway":{"modelId":"Qwen/Qwen3.5-397B-A17B","providerModelId":"qwen3.5-397b-a17b"},"together":{"modelId":"Qwen/Qwen3.5-9B","providerModelId":"Qwen/Qwen3.5-9B"},"zai-org":{"modelId":"zai-org/GLM-4.5V","providerModelId":"glm-4.5v"}} }
 conversational />
 
 

docs/inference-providers/tasks/zero-shot-classification.md

@@ -22,6 +22,7 @@ Zero-shot text classification is super useful to try out classification with zer
 
 ### Recommended models
 
+- [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli): Powerful zero-shot text classification model.
 - [MoritzLaurer/ModernBERT-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/ModernBERT-large-zeroshot-v2.0): Cutting-edge zero-shot multilingual text classification model.
 
 Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=zero-shot-classification&sort=trending).
@@ -31,7 +32,7 @@ Explore all available models and find the one that suits you best [here](https:/
 
 <InferenceSnippet
     pipeline=zero-shot-classification
-    providersMapping={ {"hf-inference":{"modelId":"MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7","providerModelId":"MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7"}} }
+    providersMapping={ {"hf-inference":{"modelId":"facebook/bart-large-mnli","providerModelId":"facebook/bart-large-mnli"}} }
 />