Cambrian-1 Models
Collection
6 items • Updated • 21
How to use from
SGLangUse 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 "nyu-visionx/cambrian-8b" \
--host 0.0.0.0 \
--port 30000# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "nyu-visionx/cambrian-8b",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'Quick Links
Cambrian Model Card
Model details
Model type: Cambrian is an open-source Multimodal LLM with vision-centric designs.
Model date: Cambrian-1-8B was trained in June 2024.
Paper or resources for more information:
License
Llama 3 is licensed under the LLAMA 3 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
Where to send questions or comments about the model: https://github.com/cambrian-mllm/cambrian/issues
Training dataset
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Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "nyu-visionx/cambrian-8b" \ --host 0.0.0.0 \ --port 30000# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nyu-visionx/cambrian-8b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'