--- inference: false pipeline_tag: image-text-to-text ---

# ShareGPT4V-7B Model Card ## Model details **Model type:** ShareGPT4V-7B is an open-source chatbot trained by fine-tuning CLP vision tower and LLaMA/Vicuna on GPT4-Vision-assisted [ShareGPT4V](https://huggingface.co./datasets/Lin-Chen/ShareGPT4V) data and LLaVA instruction-tuning data. **Model date:** ShareGPT4V-7B was trained in Nov 2023. **Paper or resources for more information:** [[Project](https://ShareGPT4V.github.io/)] [[Paper](https://huggingface.co./papers/2311.12793)] [[Code](https://github.com/ShareGPT4Omni/ShareGPT4V)] ## Usage You can directly utilize this model as we provide in our [[repository](https://github.com/ShareGPT4Omni/ShareGPT4V)]. Moreover, you can modify the architecture name from "Share4VLlamaForCausalLM" to "LLaVALlamaForCausalLM" and the model_type keyword from "share4v" to "llava" in our config file and seamlessly load our model in the [[LLaVA repository](https://github.com/haotian-liu/LLaVA)]. ## License Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved. ## Intended use **Primary intended uses:** The primary use of ShareGPT4V-7B is research on large multimodal models and chatbots. **Primary intended users:** The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence. ## Training dataset - 1.2M high-quality image-text pairs, i.e., ShareGPT4V-PT data - 100K GPT4-Vision-generated image-text pairs - LLaVA instruction-tuning data ## Evaluation dataset A collection of 11 benchmarks