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---
inference: false
pipeline_tag: image-text-to-text
---
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# 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. |