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

# AVG-LLaVA Model Card ## Model details **Model type:** AVG-LLaVA is an open-source LMM that can adaptively select the appropriate visual granularity based on the input image and instruction. It is an auto-regressive language model, based on the transformer architecture. Base LLM: [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) **Paper or resources for more information:** https://arxiv.org/abs/2410.02745 ## License Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved. **Where to send questions or comments about the model:** https://github.com/DeepLearnXMU/AVG-LLaVA/issues ## Intended use **Primary intended uses:** The primary use of LLaVA 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 - ShareGPT4V Mix665K - 200K GPT4V-generated instruction data (ALLaVA) - 200K various VQA data ## Evaluation dataset A collection of 11 benchmarks, including general VQA benchmarks, text-oriented VQA benchmarks, and general multimodal benchmarks.