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Use HF papers (#38184)

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* Use hf papers

* Hugging Face papers

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Quentin Gallouédec
2025-06-13 13:07:09 +02:00
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docs/source/en/model_doc/llava.md
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LLaVa is an open-source chatbot trained by fine-tuning LlamA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture. In other words, it is an multi-modal version of LLMs fine-tuned for chat / instructions.
The LLaVa model was proposed in [Visual Instruction Tuning](https://arxiv.org/abs/2304.08485) and improved in [Improved Baselines with Visual Instruction Tuning](https://arxiv.org/pdf/2310.03744) by Haotian Liu, Chunyuan Li, Yuheng Li and Yong Jae Lee.
The LLaVa model was proposed in [Visual Instruction Tuning](https://huggingface.co/papers/2304.08485) and improved in [Improved Baselines with Visual Instruction Tuning](https://huggingface.co/papers/2310.03744) by Haotian Liu, Chunyuan Li, Yuheng Li and Yong Jae Lee.
The abstract from the paper is the following:
@@ -35,7 +35,7 @@ The abstract from the paper is the following:
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/llava_architecture.jpg"
alt="drawing" width="600"/>
<small> LLaVa architecture. Taken from the <a href="https://arxiv.org/abs/2304.08485">original paper.</a> </small>
<small> LLaVa architecture. Taken from the <a href="https://huggingface.co/papers/2304.08485">original paper.</a> </small>
This model was contributed by [ArthurZ](https://huggingface.co/ArthurZ) and [ybelkada](https://huggingface.co/ybelkada).
The original code can be found [here](https://github.com/haotian-liu/LLaVA/tree/main/llava).