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Zery
/
MV-LLaVA-7B

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Transformers
PyTorch
English
share4v
text-generation
Model card Files
xet
 Community
1
How to use from
vLLM
Install from pip and serve model 
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Zery/MV-LLaVA-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Zery/MV-LLaVA-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker 
docker model run hf.co/Zery/MV-LLaVA-7B
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MV-LLaVA-7B Model Card

Model details

Model type: MV-LLaVA-7B is an open-source chatbot for 3D multi-view images trained by fine-tuning CLIP vision tower and LLaMA/Vicuna on GPT4-Vision-assisted BS-Objaverse data and ShareGPT4V data.

Model date: MV-LLaVA-7B was trained in Apr, 2024.

Paper or resources for more information: [Project] [Paper] [Code]

Usage

You can directly utilize this model as we provide in our [repository].

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 for 3D content. 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 ShareGPT4V-PT data
  • 30K GPT4-Vision-generated multi-view image-text pairs
  • LLaVA instruction-tuning data
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Datasets used to train Zery/MV-LLaVA-7B

Collection including Zery/MV-LLaVA-7B

Paper for Zery/MV-LLaVA-7B