Text Generation
Transformers
PyTorch
Chinese
English
bloom
feature-extraction
text2text-generation
text-generation-inference
Instructions to use BelleGroup/BELLE-7B-0.2M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BelleGroup/BELLE-7B-0.2M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BelleGroup/BELLE-7B-0.2M")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BelleGroup/BELLE-7B-0.2M") model = AutoModel.from_pretrained("BelleGroup/BELLE-7B-0.2M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use BelleGroup/BELLE-7B-0.2M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BelleGroup/BELLE-7B-0.2M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BelleGroup/BELLE-7B-0.2M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BelleGroup/BELLE-7B-0.2M
- SGLang
How to use BelleGroup/BELLE-7B-0.2M 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 "BelleGroup/BELLE-7B-0.2M" \ --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": "BelleGroup/BELLE-7B-0.2M", "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 "BelleGroup/BELLE-7B-0.2M" \ --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": "BelleGroup/BELLE-7B-0.2M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BelleGroup/BELLE-7B-0.2M with Docker Model Runner:
docker model run hf.co/BelleGroup/BELLE-7B-0.2M
- Xet hash:
- 9568919d06744a5346c675e2cfa5581ddb6690b8780629a18532e55a613db09e
- Size of remote file:
- 28.3 GB
- SHA256:
- 8af7dde60354a273741c39634580841b8c864ff58c5e9154ed8b9079bab6921e
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