Instructions to use Lin-Chen/ShareGPT4V-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lin-Chen/ShareGPT4V-13B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Lin-Chen/ShareGPT4V-13B")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Lin-Chen/ShareGPT4V-13B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Lin-Chen/ShareGPT4V-13B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Lin-Chen/ShareGPT4V-13B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Lin-Chen/ShareGPT4V-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Lin-Chen/ShareGPT4V-13B
- SGLang
How to use Lin-Chen/ShareGPT4V-13B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Lin-Chen/ShareGPT4V-13B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Lin-Chen/ShareGPT4V-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Lin-Chen/ShareGPT4V-13B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Lin-Chen/ShareGPT4V-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Lin-Chen/ShareGPT4V-13B with Docker Model Runner:
docker model run hf.co/Lin-Chen/ShareGPT4V-13B
Update README.md
Browse files
README.md
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ShareGPT4V-13B was trained in Nov 2023.
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**Paper or resources for more information:**
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[[Project](https://ShareGPT4V.github.io/)] [[Paper](https://huggingface.co/papers/2311.12793)] [[Code](https://github.com/
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## Usage
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You can directly utilize this model as we provide in our [[repository](https://github.com/
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## License
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Llama 2 is licensed under the LLAMA 2 Community License,
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ShareGPT4V-13B was trained in Nov 2023.
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**Paper or resources for more information:**
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[[Project](https://ShareGPT4V.github.io/)] [[Paper](https://huggingface.co/papers/2311.12793)] [[Code](https://github.com/ShareGPT4Omni/ShareGPT4V)]
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## Usage
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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)].
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## License
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Llama 2 is licensed under the LLAMA 2 Community License,
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