Instructions to use liya0121/my_finetune_0121 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liya0121/my_finetune_0121 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="liya0121/my_finetune_0121")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("liya0121/my_finetune_0121", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use liya0121/my_finetune_0121 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "liya0121/my_finetune_0121" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "liya0121/my_finetune_0121", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/liya0121/my_finetune_0121
- SGLang
How to use liya0121/my_finetune_0121 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 "liya0121/my_finetune_0121" \ --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": "liya0121/my_finetune_0121", "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 "liya0121/my_finetune_0121" \ --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": "liya0121/my_finetune_0121", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use liya0121/my_finetune_0121 with Docker Model Runner:
docker model run hf.co/liya0121/my_finetune_0121
Download optimizer.pt from liya0121/my_finetune_0121: direct link, hf CLI and curl.
- Browser
- Download file 6.12 GB
-
https://huggingface.co/liya0121/my_finetune_0121/resolve/main/optimizer.pt
- Command line
-
hf download hf://liya0121/my_finetune_0121/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/liya0121/my_finetune_0121/resolve/main/optimizer.pt
6.12 GB
- Xet hash:
- 0d0da1ec39239bbe854e60e8a26607c9f6b42b24c4c03fbdbe47514a95c5fd04
- Size of remote file:
- 6.12 GB
- SHA256:
- 9db4ff8a5a778d23bb97367571c6b9eb17189938f38df135a0c94fe00fe25651
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