Instructions to use wangjin2000/git-base-finetune-Aug112023_05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wangjin2000/git-base-finetune-Aug112023_05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="wangjin2000/git-base-finetune-Aug112023_05")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("wangjin2000/git-base-finetune-Aug112023_05") model = AutoModelForMultimodalLM.from_pretrained("wangjin2000/git-base-finetune-Aug112023_05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use wangjin2000/git-base-finetune-Aug112023_05 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "wangjin2000/git-base-finetune-Aug112023_05" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wangjin2000/git-base-finetune-Aug112023_05", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/wangjin2000/git-base-finetune-Aug112023_05
- SGLang
How to use wangjin2000/git-base-finetune-Aug112023_05 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 "wangjin2000/git-base-finetune-Aug112023_05" \ --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": "wangjin2000/git-base-finetune-Aug112023_05", "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 "wangjin2000/git-base-finetune-Aug112023_05" \ --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": "wangjin2000/git-base-finetune-Aug112023_05", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use wangjin2000/git-base-finetune-Aug112023_05 with Docker Model Runner:
docker model run hf.co/wangjin2000/git-base-finetune-Aug112023_05
- Xet hash:
- 977cdf63aae13b28c6a0e8ca247daeb1ef0769a17125a2732a910695324b4baf
- Size of remote file:
- 707 MB
- SHA256:
- 9576257c0392953c1dc799ee72326dfd2c077caf78d76ffec6f576c80e40ec23
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