Instructions to use LocalWisdom/Penny-Alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalWisdom/Penny-Alpha with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LocalWisdom/Penny-Alpha", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("LocalWisdom/Penny-Alpha", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LocalWisdom/Penny-Alpha with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LocalWisdom/Penny-Alpha" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LocalWisdom/Penny-Alpha", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LocalWisdom/Penny-Alpha
- SGLang
How to use LocalWisdom/Penny-Alpha 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 "LocalWisdom/Penny-Alpha" \ --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": "LocalWisdom/Penny-Alpha", "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 "LocalWisdom/Penny-Alpha" \ --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": "LocalWisdom/Penny-Alpha", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LocalWisdom/Penny-Alpha with Docker Model Runner:
docker model run hf.co/LocalWisdom/Penny-Alpha
Download model.pt from LocalWisdom/Penny-Alpha: direct link, hf CLI and curl.
- Browser
- Download file 236 MB
-
https://huggingface.co/LocalWisdom/Penny-Alpha/resolve/main/model.pt
- Command line
-
hf download hf://LocalWisdom/Penny-Alpha/model.pt
-
curl -L -o model.pt https://huggingface.co/LocalWisdom/Penny-Alpha/resolve/main/model.pt
236 MB
- Xet hash:
- 01bf085a0ff5c011f2e26c1bf90a3dec0631370be53dfa1b894612d36b443160
- Size of remote file:
- 236 MB
- SHA256:
- 0e52948fd27d204b5ea2baee885979baf9732f8c897808b9fbe4badf4c5ecd54
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