Small fixes for supported models (#2471)
* Small improvements for docs * Update _toctree.yml * Updating the doc (we keep the list actually). --------- Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
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title: Text Generation Inference
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- local: quicktour
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title: Quick Tour
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- local: supported_models
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title: Supported Models
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- local: installation_nvidia
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title: Using TGI with Nvidia GPUs
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- local: installation_amd
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title: Using TGI with Intel GPUs
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- local: installation
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title: Installation from source
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- local: supported_models
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title: Supported Models and Hardware
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- local: architecture
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title: Internal Architecture
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- local: usage_statistics
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# Supported Models and Hardware
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# Supported Models
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Text Generation Inference enables serving optimized models on specific hardware for the highest performance. The following sections list which models (VLMs & LLMs) are supported.
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## Supported Models
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Text Generation Inference enables serving optimized models. The following sections list which models (VLMs & LLMs) are supported.
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- [Deepseek V2](https://huggingface.co/deepseek-ai/DeepSeek-V2)
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- [Idefics 2](https://huggingface.co/HuggingFaceM4/idefics2-8b) (Multimodal)
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@ -38,6 +36,7 @@ Text Generation Inference enables serving optimized models on specific hardware
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- [Mllama](https://huggingface.co/meta-llama/Llama-3.2-11B-Vision-Instruct) (Multimodal)
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If the above list lacks the model you would like to serve, depending on the model's pipeline type, you can try to initialize and serve the model anyways to see how well it performs, but performance isn't guaranteed for non-optimized models:
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```python
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@ -5,14 +5,13 @@ import json
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import os
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TEMPLATE = """
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# Supported Models and Hardware
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# Supported Models
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Text Generation Inference enables serving optimized models on specific hardware for the highest performance. The following sections list which models (VLMs & LLMs) are supported.
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## Supported Models
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Text Generation Inference enables serving optimized models. The following sections list which models (VLMs & LLMs) are supported.
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SUPPORTED_MODELS
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If the above list lacks the model you would like to serve, depending on the model's pipeline type, you can try to initialize and serve the model anyways to see how well it performs, but performance isn't guaranteed for non-optimized models:
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```python
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