How to use from
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 "hoskinson-center/proofGPT-v0.1" \
    --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": "hoskinson-center/proofGPT-v0.1",
		"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 "hoskinson-center/proofGPT-v0.1" \
        --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": "hoskinson-center/proofGPT-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Quick Links

ProofGPT-v0.1

Model Description

ProofGPT-v0.1 is a 1.3B parameter language model based on the GPT-NeoX architecture and trained on the proof-pile (v1.1). We initiailized training with pythia-1.3b weights, a precursor to the pythia-1.4b model that has roughly equivalent performance.

Detailed evaluations coming soon :)

Note: Commit 3bcdc4e replaced the weights with a model trained on proof-pile v1.1, as opposed to previous commits which were trained on v1.0. Commit 9695b51 updated the tokenizer to have bos, eos, and unk tokens.

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