Instructions to use LesterCerioli/LLM-GO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LesterCerioli/LLM-GO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LesterCerioli/LLM-GO")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LesterCerioli/LLM-GO", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LesterCerioli/LLM-GO with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LesterCerioli/LLM-GO" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LesterCerioli/LLM-GO", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LesterCerioli/LLM-GO
- SGLang
How to use LesterCerioli/LLM-GO 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 "LesterCerioli/LLM-GO" \ --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": "LesterCerioli/LLM-GO", "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 "LesterCerioli/LLM-GO" \ --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": "LesterCerioli/LLM-GO", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LesterCerioli/LLM-GO with Docker Model Runner:
docker model run hf.co/LesterCerioli/LLM-GO
| """CLI: push a checkpoint to Hugging Face Hub.""" | |
| import os | |
| import click | |
| from llm_go.deployment.hf_uploader import HuggingFaceUploader | |
| def main(ckpt_dir, tok_dir, repo_id, token, private, message): | |
| """Deploy GoLLM to Hugging Face Hub.""" | |
| uploader = HuggingFaceUploader(repo_id=repo_id, hf_token=token, private=private) | |
| url = uploader.upload( | |
| checkpoint_dir=ckpt_dir, | |
| tokenizer_dir=tok_dir, | |
| commit_message=message, | |
| ) | |
| click.echo(f"Model live at: {url}") | |