Navigating Human Language Models with Synthetic Agents
Paper • 2008.04162 • Published
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")How to use pgfeldman/GPT2-chess with vLLM:
# 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
}'docker model run hf.co/pgfeldman/GPT2-chess
How to use pgfeldman/GPT2-chess with SGLang:
# 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
}'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
}'How to use pgfeldman/GPT2-chess with Docker Model Runner:
docker model run hf.co/pgfeldman/GPT2-chess
Model trained on chess "narratives" created from PGN notation from a large set of games downloaded from The Week in Chess (https://theweekinchess.com/). A script was run to convert the PGN notation to english text, and the model was finetuned on that. The approach is described in the paper Navigating Human Language Models with Synthetic Agents.
@misc{feldman2020navigating,
title={Navigating Human Language Models with Synthetic Agents},
author={Philip Feldman and Antonio Bucchiarone},
year={2020},
eprint={2008.04162},
archivePrefix={arXiv},
primaryClass={cs.AI}
}