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--- |
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inference: false |
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license: llama2 |
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pipeline_tag: image-to-text |
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--- |
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# DenseConnector-with-mgm-7B Model Card |
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## Model details |
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**Model type:** |
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DenseConnector is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. |
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It is an auto-regressive language model, based on the transformer architecture. |
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**Model info:** |
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DenseConnector-with-mgm-7B was trained in 05/2024. |
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**Paper or resources for more information:** |
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https://github.com/HJYao00/DenseConnector |
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**Paper on Hugging Face:** |
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[arxiv.org/abs/2405.13800](https://arxiv.org/abs/2405.13800) |
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**Training dataset:** |
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This model is trained on [MGM](https://github.com/dvlab-research/MGM/tree/main) dataset. |
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**Large Language Model:** |
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Vicuna-7B |
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**How to inference:** |
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This model was trained based on the MGM codebase. Please replace mgm_arch.py in MGM to test our model. |
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## License |
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Llama 2 is licensed under the LLAMA 2 Community License, |
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Copyright (c) Meta Platforms, Inc. All Rights Reserved. |
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**Where to send questions or comments about the model:** |
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https://github.com/HJYao00/DenseConnector/issues |
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## Intended use |
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**Primary intended uses:** |
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The primary use of DenseConnector is research on large multimodal models and chatbots. |
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**Primary intended users:** |
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The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence. |
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