Instructions to use breadlicker45/MusePy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breadlicker45/MusePy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="breadlicker45/MusePy")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("breadlicker45/MusePy") model = AutoModelForCausalLM.from_pretrained("breadlicker45/MusePy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use breadlicker45/MusePy with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "breadlicker45/MusePy" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "breadlicker45/MusePy", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/breadlicker45/MusePy
- SGLang
How to use breadlicker45/MusePy 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 "breadlicker45/MusePy" \ --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": "breadlicker45/MusePy", "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 "breadlicker45/MusePy" \ --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": "breadlicker45/MusePy", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use breadlicker45/MusePy with Docker Model Runner:
docker model run hf.co/breadlicker45/MusePy
Commit History
Update README.md c6e9c3d
Update README.md 6ac9821
Update README.md 31049f5
Update README.md 6ec7af8
Update README.md a044027
Update README.md 8d10813
Update README.md 39ff74e
Update README.md 00939bf
Update README.md 89bad15
Update README.md ccf490e
Update README.md 321353b
Update README.md 17d570b
Update README.md 582e4fb
Update README.md dfdd910
Update README.md 06d021e
Update README.md b2ad937
Update README.md 157d57a
Update README.md 1829e27
Update README.md a9efb8e
Update README.md 722570b
Update README.md 04107ea
initial commit b3c128a
matthew null commited on