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@@ -19,6 +19,12 @@ It is _**the largest open-source vision/vision-language foundation model (14B)**
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/QmVXOyr4uFQLx5Q-WLn9-.png)
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  ## Model details
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  **Model type:**
@@ -56,12 +62,6 @@ The primary intended users of the model are researchers and hobbyists in compute
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  ## Evaluation dataset
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  A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.
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- ## How to Run?
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- Please refer to this [README](https://github.com/OpenGVLab/InternVL/tree/main/llava#internvl-for-multimodal-dialogue-using-llava) to run this model.
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- Note: We have retained the original documentation of LLaVA 1.5 as a more detailed manual. In most cases, you will only need to refer to the new documentation that we have added.
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  ## Acknowledgement
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  This model card is adapted from [LLaVA's model card](https://huggingface.co/liuhaotian/llava-v1.5-13b). Thanks for their awesome work!
 
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/QmVXOyr4uFQLx5Q-WLn9-.png)
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+ ## How to Run?
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+ Please refer to this [README](https://github.com/OpenGVLab/InternVL/tree/main/llava#internvl-for-multimodal-dialogue-using-llava) to run this model.
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+ Note: We have retained the original documentation of LLaVA 1.5 as a more detailed manual. In most cases, you will only need to refer to the new documentation that we have added.
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  ## Model details
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  **Model type:**
 
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  ## Evaluation dataset
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  A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.
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  ## Acknowledgement
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  This model card is adapted from [LLaVA's model card](https://huggingface.co/liuhaotian/llava-v1.5-13b). Thanks for their awesome work!