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: interactive Go code generation.""" | |
| import click | |
| import tensorflow as tf | |
| from llm_go.model.transformer import GoLLM | |
| from llm_go.tokenizer.go_tokenizer import GoTokenizer | |
| def main(model_dir, tok_dir, prompt, max_tokens, temperature, top_p, top_k): | |
| """Generate Go code with a trained GoLLM checkpoint.""" | |
| tok = GoTokenizer.load(tok_dir) | |
| model = GoLLM.from_pretrained(model_dir) | |
| def generate(text: str) -> str: | |
| ids = tok.encode(text) | |
| out = model.generate( | |
| tf.constant([ids], dtype=tf.int32), | |
| max_new_tokens=max_tokens, | |
| temperature=temperature, | |
| top_p=top_p, | |
| top_k=top_k, | |
| ) | |
| return tok.decode(out[0].numpy().tolist()) | |
| if prompt: | |
| click.echo(generate(prompt)) | |
| else: | |
| click.echo("GoLLM interactive shell. Type 'exit' to quit.\n") | |
| while True: | |
| try: | |
| text = click.prompt(">>> ") | |
| except (EOFError, KeyboardInterrupt): | |
| break | |
| if text.strip().lower() in {"exit", "quit"}: | |
| break | |
| click.echo(generate(text)) | |