doubility123
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README.md
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@@ -20,7 +20,7 @@ Haoyu Lu*, Wen Liu*, Bo Zhang**, Bingxuan Wang, Kai Dong, Bo Liu, Jingxiang Sun,
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### 2. Model Summary
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DeepSeek-VL-1.3b-chat is a tiny vision-language model. It uses the [SigLIP-L](https://huggingface.co/timm/ViT-L-16-SigLIP-384) as the vision encoder supporting 384 x 384 image input
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and is constructed based on the DeepSeek-LLM-1.3b-base which is trained on an approximate corpus of 500B text tokens. The whole DeepSeek-1.3b-base model is finally trained around 400B vision-language tokens.
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The DeepSeek-VL-1.3b-chat is an instructed version based on [DeepSeek-VL-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-vl-1.3b-base).
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### 2. Model Summary
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DeepSeek-VL-1.3b-chat is a tiny vision-language model. It uses the [SigLIP-L](https://huggingface.co/timm/ViT-L-16-SigLIP-384) as the vision encoder supporting 384 x 384 image input
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and is constructed based on the DeepSeek-LLM-1.3b-base which is trained on an approximate corpus of 500B text tokens. The whole DeepSeek-VL-1.3b-base model is finally trained around 400B vision-language tokens.
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The DeepSeek-VL-1.3b-chat is an instructed version based on [DeepSeek-VL-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-vl-1.3b-base).
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