Instructions to use WangZeJun/bloom-396m-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WangZeJun/bloom-396m-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="WangZeJun/bloom-396m-chat")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("WangZeJun/bloom-396m-chat") model = AutoModelForCausalLM.from_pretrained("WangZeJun/bloom-396m-chat") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use WangZeJun/bloom-396m-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "WangZeJun/bloom-396m-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WangZeJun/bloom-396m-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/WangZeJun/bloom-396m-chat
- SGLang
How to use WangZeJun/bloom-396m-chat 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 "WangZeJun/bloom-396m-chat" \ --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": "WangZeJun/bloom-396m-chat", "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 "WangZeJun/bloom-396m-chat" \ --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": "WangZeJun/bloom-396m-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use WangZeJun/bloom-396m-chat with Docker Model Runner:
docker model run hf.co/WangZeJun/bloom-396m-chat
- Xet hash:
- 9846cd78365f458080401054840d2c25447a4d2449407ab053a4d302f79ee558
- Size of remote file:
- 1.4 GB
- SHA256:
- dc774a3591ee1ecc0509de7ab98066cae816b82694f0e1b3312321205f80490e
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