Instructions to use pgfeldman/GPT2-chess with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pgfeldman/GPT2-chess with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pgfeldman/GPT2-chess")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("pgfeldman/GPT2-chess") model = AutoModelForCausalLM.from_pretrained("pgfeldman/GPT2-chess") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pgfeldman/GPT2-chess with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pgfeldman/GPT2-chess" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pgfeldman/GPT2-chess", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pgfeldman/GPT2-chess
- SGLang
How to use pgfeldman/GPT2-chess 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 "pgfeldman/GPT2-chess" \ --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": "pgfeldman/GPT2-chess", "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 "pgfeldman/GPT2-chess" \ --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": "pgfeldman/GPT2-chess", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pgfeldman/GPT2-chess with Docker Model Runner:
docker model run hf.co/pgfeldman/GPT2-chess
Update README.md
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README.md
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@@ -9,4 +9,16 @@ Model trained on chess "narratives" created from PGN notation from a large set o
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* "White/Black moves X from Y" // X is the piece (pawn, bishop, knight, rook, queen, king) and Y is the square (e.g. e2)
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* "The game begins as white uses the X opening" // X is a known opening move such as Sicilian
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* "White moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king)
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* "Black moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king)
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* "White/Black moves X from Y" // X is the piece (pawn, bishop, knight, rook, queen, king) and Y is the square (e.g. e2)
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* "The game begins as white uses the X opening" // X is a known opening move such as Sicilian
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* "White moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king)
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* "Black moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king)
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# Citation:
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```
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@misc{feldman2020navigating,
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title={Navigating Human Language Models with Synthetic Agents},
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author={Philip Feldman and Antonio Bucchiarone},
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year={2020},
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eprint={2008.04162},
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archivePrefix={arXiv},
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primaryClass={cs.AI}
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}
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```
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