Instructions to use TheRoblocCreators/LuaCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheRoblocCreators/LuaCoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheRoblocCreators/LuaCoder")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheRoblocCreators/LuaCoder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TheRoblocCreators/LuaCoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheRoblocCreators/LuaCoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheRoblocCreators/LuaCoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheRoblocCreators/LuaCoder
- SGLang
How to use TheRoblocCreators/LuaCoder 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 "TheRoblocCreators/LuaCoder" \ --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": "TheRoblocCreators/LuaCoder", "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 "TheRoblocCreators/LuaCoder" \ --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": "TheRoblocCreators/LuaCoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheRoblocCreators/LuaCoder with Docker Model Runner:
docker model run hf.co/TheRoblocCreators/LuaCoder
| license: openrail | |
| datasets: | |
| - nick007x/github-code-2025 | |
| - CoIR-Retrieval/CodeSearchNet | |
| - TorpedoSoftware/Roblox-Luau-Reasoning-v1.0 | |
| language: | |
| - en | |
| - fr | |
| - ar | |
| - zh | |
| - hi | |
| - es | |
| - bn | |
| - pt | |
| - ru | |
| - ur | |
| metrics: | |
| - accuracy | |
| - code_eval | |
| - codeparrot/apps_metric | |
| base_model: | |
| - mistralai/Mistral-7B-Instruct-v0.3 | |
| - zai-org/GLM-4.6 | |
| - tiiuae/Falcon-H1-1.5B-Deep-Instruct | |
| - deepseek-ai/DeepSeek-V3.1 | |
| - deepseek-ai/DeepSeek-V3.2-Exp | |
| - google/gemma-3-27b-it | |
| - akhaliq/gpt-5 | |
| - xai-org/grok-2 | |
| new_version: deepseek-ai/DeepSeek-OCR | |
| pipeline_tag: text-generation | |
| library_name: transformers | |
| tags: | |
| - code | |