Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+metrics:
+- accuracy
+base_model:
+- meta-llama/Llama-3.1-8B-Instruct
+pipeline_tag: visual-question-answering
+---
+
+# MMEvol Model Card
+
+## Model Details
+
+Here are the pretrained weights and instruction tuning weights
+| Model            | Pretrained Projector | Base LLM  | PT Data                                                      | IT Data | Download |
+| ---------------- | -------------------- | --------- | ------------------------------------------------------------ | ------- | -------- |
+| MMEvol-LLaMA3-8B | [mm_projector](https://huggingface.co/Tongyi-ConvAI/MMEvol/tree/main/llama3) | LLaMA3-8B | [LLaVA-Pretrain](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain) | MMEvol | [ckpt](https://huggingface.co/Tongyi-ConvAI/MMEvol/tree/main/llama3)|
+
+## Training dataset
+- [480k MMEvol Curated Instruction Tuning Data](https://huggingface.co/datasets/Tongyi-ConvAI/MMEvol).
+
+## Performance
+
+### VLMEvalKit Support (OpenCompass)
+
+| Model            | MME_C | MMStar | HallBench | MathVista_mini | MMMU_val | AI2D | POPE | BLINK | RWQA |
+| ---------------- | ----- | ------ | --------- | -------------- | -------- | ---- | ---- | ----- | ---- |
+| MMEvol-LLaMA3-8B | 47.8  | 50.1   | 62.3      | 50.0           | 40.8     | 73.9 | 86.8 | 46.4  | 62.6 |
+
+### VLMEvalKit Not Support (VQADataSet)
+
+| Model            | VQA_v2 | GQA  | MIA  | MMSInst |
+| ---------------- | ------ | ---- | ---- | ------- |
+| MMEvol-LLaMA3-8B | 83.4   | 65.0 | 78.8 | 32.3    |
+
+
+## Paper or resources for more information
+- Page: https://mmevol.github.io/
+- arXiv: https://arxiv.org/pdf/2409.05840
+
+## License
+Llama 3 is licensed under the LLAMA 3 Community License, 
+Copyright (c) Meta Platforms, Inc. All Rights Reserved.
+
+## Contact us if you have any questions
+
+- Run Luo — r.luo@siat.ac.cn
+- Haonan Zhang — zchiowal@gmail.com