Instructions to use LLM-course/chess-Sunxt25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LLM-course/chess-Sunxt25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LLM-course/chess-Sunxt25")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("LLM-course/chess-Sunxt25", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LLM-course/chess-Sunxt25 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LLM-course/chess-Sunxt25" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LLM-course/chess-Sunxt25", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LLM-course/chess-Sunxt25
- SGLang
How to use LLM-course/chess-Sunxt25 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 "LLM-course/chess-Sunxt25" \ --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": "LLM-course/chess-Sunxt25", "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 "LLM-course/chess-Sunxt25" \ --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": "LLM-course/chess-Sunxt25", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LLM-course/chess-Sunxt25 with Docker Model Runner:
docker model run hf.co/LLM-course/chess-Sunxt25
Chess Challenge submission by Sunxt25
Browse files- model.safetensors +1 -1
- tokenizer_config.json +0 -6
model.safetensors
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tokenizer_config.json
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"single_word": false,
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"special": true
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}
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},
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"auto_map": {
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"AutoTokenizer": [
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"tokenizer.ChessTokenizer",
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]
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},
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"bos_token": "[BOS]",
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"clean_up_tokenization_spaces": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "[BOS]",
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"clean_up_tokenization_spaces": false,
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