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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LesterCerioli/LLM-GO", device_map="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
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a58ece3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | """CLI: push a checkpoint to Hugging Face Hub."""
import os
import click
from llm_go.deployment.hf_uploader import HuggingFaceUploader
@click.command()
@click.option("--ckpt-dir", required=True, help="Checkpoint directory to upload")
@click.option("--tok-dir", required=True, help="Tokenizer directory")
@click.option("--repo-id", required=True, help="HF repo, e.g. myorg/llm-go-350m")
@click.option("--token", default=lambda: os.environ.get("HF_TOKEN", ""))
@click.option("--private/--public", default=False)
@click.option("--message", default="Upload GoLLM checkpoint", show_default=True)
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}")
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