Instructions to use temporary0-0name/pretrained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use temporary0-0name/pretrained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="temporary0-0name/pretrained_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("temporary0-0name/pretrained_model") model = AutoModelForCausalLM.from_pretrained("temporary0-0name/pretrained_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use temporary0-0name/pretrained_model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "temporary0-0name/pretrained_model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "temporary0-0name/pretrained_model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/temporary0-0name/pretrained_model
- SGLang
How to use temporary0-0name/pretrained_model 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 "temporary0-0name/pretrained_model" \ --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": "temporary0-0name/pretrained_model", "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 "temporary0-0name/pretrained_model" \ --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": "temporary0-0name/pretrained_model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use temporary0-0name/pretrained_model with Docker Model Runner:
docker model run hf.co/temporary0-0name/pretrained_model
Commit History
-
End of training
71a8b81 -
Training in progress, step 100
cc906bf -
End of training
d77b1bf -
Training in progress, step 100
5ac1cd1 -
End of training
312a80f -
Training in progress, step 100
47f9fa4 -
Upload tokenizer
e1e4b67 -
Upload model
2058cf1 -
Upload tokenizer
0a2b62f -
Upload model
d776d31 -
Upload tokenizer
c84eb84 -
Upload model
4c146c8 -
initial commit
e1c9e6b