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README.md
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@@ -16,30 +16,6 @@ This repo contains the **biomedicine MLLM developed from LLaVA-NeXT-Llama3-8B**
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The main project page is: [Adapt-MLLM-to-Domains](https://huggingface.co/AdaptLLM/Adapt-MLLM-to-Domains/edit/main/README.md)
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We investigate domain adaptation of MLLMs through post-training, focusing on data synthesis, training pipelines, and task evaluation.
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**(1) Data Synthesis**: Using open-source models, we develop a visual instruction synthesizer that effectively generates diverse visual instruction tasks from domain-specific image-caption pairs. **Our synthetic tasks surpass those generated by manual rules, GPT-4, and GPT-4V in enhancing the domain-specific performance of MLLMs.**
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**(2) Training Pipeline**: While the two-stage training--initially on image-caption pairs followed by visual instruction tasks--is commonly adopted for developing general MLLMs, we apply a single-stage training pipeline to enhance task diversity for domain-specific post-training.
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**(3) Task Evaluation**: We conduct experiments in two domains, biomedicine and food, by post-training MLLMs of different sources and scales (e.g., Qwen2-VL-2B, LLaVA-v1.6-8B, Llama-3.2-11B), and then evaluating MLLM performance on various domain-specific tasks.
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<p align='center'>
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<img src="https://cdn-uploads.huggingface.co/production/uploads/650801ced5578ef7e20b33d4/-Jp7pAsCR2Tj4WwfwsbCo.png" width="600">
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</p>
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## Resources
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**🤗 We share our data and models with example usages, feel free to open any issues or discussions! 🤗**
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| Model | Repo ID in HF 🤗 | Domain | Base Model | Training Data | Evaluation Benchmark |
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|:----------------------------------------------------------------------------|:--------------------------------------------|:--------------|:-------------------------|:------------------------------------------------------------------------------------------------|-----------------------|
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| [Visual Instruction Synthesizer](https://huggingface.co/AdaptLLM/visual-instruction-synthesizer) | AdaptLLM/visual-instruction-synthesizer | - | open-llava-next-llama3-8b | VisionFLAN and ALLaVA | - |
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| [AdaMLLM-med-2B](https://huggingface.co/AdaptLLM/biomed-Qwen2-VL-2B-Instruct) | AdaptLLM/biomed-Qwen2-VL-2B-Instruct | Biomedicine | Qwen2-VL-2B-Instruct | [biomed-visual-instructions](https://huggingface.co/datasets/AdaptLLM/biomed-visual-instructions) | [biomed-VQA-benchmark](https://huggingface.co/datasets/AdaptLLM/biomed-VQA-benchmark) |
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| [AdaMLLM-food-2B](https://huggingface.co/AdaptLLM/food-Qwen2-VL-2B-Instruct) | AdaptLLM/food-Qwen2-VL-2B-Instruct | Food | Qwen2-VL-2B-Instruct | [food-visual-instructions](https://huggingface.co/datasets/AdaptLLM/food-visual-instructions) | [food-VQA-benchmark](https://huggingface.co/datasets/AdaptLLM/food-VQA-benchmark) |
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| [AdaMLLM-med-8B](https://huggingface.co/AdaptLLM/biomed-LLaVA-NeXT-Llama3-8B) | AdaptLLM/biomed-LLaVA-NeXT-Llama3-8B | Biomedicine | open-llava-next-llama3-8b | [biomed-visual-instructions](https://huggingface.co/datasets/AdaptLLM/biomed-visual-instructions) | [biomed-VQA-benchmark](https://huggingface.co/datasets/AdaptLLM/biomed-VQA-benchmark) |
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| [AdaMLLM-food-8B](https://huggingface.co/AdaptLLM/food-LLaVA-NeXT-Llama3-8B) |AdaptLLM/food-LLaVA-NeXT-Llama3-8B | Food | open-llava-next-llama3-8b | [food-visual-instructions](https://huggingface.co/datasets/AdaptLLM/food-visual-instructions) | [food-VQA-benchmark](https://huggingface.co/datasets/AdaptLLM/food-VQA-benchmark) |
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| [AdaMLLM-med-11B](https://huggingface.co/AdaptLLM/biomed-Llama-3.2-11B-Vision-Instruct) | AdaptLLM/biomed-Llama-3.2-11B-Vision-Instruct | Biomedicine | Llama-3.2-11B-Vision-Instruct | [biomed-visual-instructions](https://huggingface.co/datasets/AdaptLLM/biomed-visual-instructions) | [biomed-VQA-benchmark](https://huggingface.co/datasets/AdaptLLM/biomed-VQA-benchmark) |
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| [AdaMLLM-food-11B](https://huggingface.co/AdaptLLM/food-Llama-3.2-11B-Vision-Instruct) | AdaptLLM/food-Llama-3.2-11B-Vision-Instruct | Food | Llama-3.2-11B-Vision-Instruct | [food-visual-instructions](https://huggingface.co/datasets/AdaptLLM/food-visual-instructions) | [food-VQA-benchmark](https://huggingface.co/datasets/AdaptLLM/food-VQA-benchmark) |
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**Code**: [https://github.com/bigai-ai/QA-Synthesizer](https://github.com/bigai-ai/QA-Synthesizer)
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## 1. To Chat with AdaMLLM
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```python
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The main project page is: [Adapt-MLLM-to-Domains](https://huggingface.co/AdaptLLM/Adapt-MLLM-to-Domains/edit/main/README.md)
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## 1. To Chat with AdaMLLM
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```python
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