Instructions to use BELLE-2/BELLE-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BELLE-2/BELLE-VL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BELLE-2/BELLE-VL", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("BELLE-2/BELLE-VL", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use BELLE-2/BELLE-VL with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BELLE-2/BELLE-VL" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BELLE-2/BELLE-VL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BELLE-2/BELLE-VL
- SGLang
How to use BELLE-2/BELLE-VL 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 "BELLE-2/BELLE-VL" \ --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": "BELLE-2/BELLE-VL", "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 "BELLE-2/BELLE-VL" \ --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": "BELLE-2/BELLE-VL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BELLE-2/BELLE-VL with Docker Model Runner:
docker model run hf.co/BELLE-2/BELLE-VL
Download pytorch_model-00001-of-00004.bin from BELLE-2/BELLE-VL: direct link, hf CLI and curl.
- Browser
- Download file 9.96 GB
-
https://huggingface.co/BELLE-2/BELLE-VL/resolve/main/pytorch_model-00001-of-00004.bin
- Command line
-
hf download hf://BELLE-2/BELLE-VL/pytorch_model-00001-of-00004.bin
-
curl -L -o pytorch_model-00001-of-00004.bin https://huggingface.co/BELLE-2/BELLE-VL/resolve/main/pytorch_model-00001-of-00004.bin
9.96 GB
- Xet hash:
- 10dc7522f3e2c1bc5a868f7d48ed523829402eabbf2f8a87c5f87f107fe9a000
- Size of remote file:
- 9.96 GB
- SHA256:
- d03a012d0e26e0a8bb1c323601120fff08c42005dbe3f121e516dcda06387874
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