Instructions to use sunfu-chou/git-base-naruto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunfu-chou/git-base-naruto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="sunfu-chou/git-base-naruto")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("sunfu-chou/git-base-naruto") model = AutoModelForMultimodalLM.from_pretrained("sunfu-chou/git-base-naruto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use sunfu-chou/git-base-naruto with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sunfu-chou/git-base-naruto" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sunfu-chou/git-base-naruto", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sunfu-chou/git-base-naruto
- SGLang
How to use sunfu-chou/git-base-naruto 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 "sunfu-chou/git-base-naruto" \ --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": "sunfu-chou/git-base-naruto", "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 "sunfu-chou/git-base-naruto" \ --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": "sunfu-chou/git-base-naruto", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use sunfu-chou/git-base-naruto with Docker Model Runner:
docker model run hf.co/sunfu-chou/git-base-naruto
- Xet hash:
- d1cc77987ae110a607012500cc01fa4501cbdd112f06aa744fa3cee7fa53fd0a
- Size of remote file:
- 4.98 kB
- SHA256:
- 64d88b6792386f6d5db9bc580cb836b48e03d35c05c2809321724a47fa7bfc72
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.