Instructions to use christopherastone/distilgpt2-proofs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christopherastone/distilgpt2-proofs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="christopherastone/distilgpt2-proofs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("christopherastone/distilgpt2-proofs") model = AutoModelForCausalLM.from_pretrained("christopherastone/distilgpt2-proofs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use christopherastone/distilgpt2-proofs with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "christopherastone/distilgpt2-proofs" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "christopherastone/distilgpt2-proofs", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/christopherastone/distilgpt2-proofs
- SGLang
How to use christopherastone/distilgpt2-proofs 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 "christopherastone/distilgpt2-proofs" \ --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": "christopherastone/distilgpt2-proofs", "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 "christopherastone/distilgpt2-proofs" \ --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": "christopherastone/distilgpt2-proofs", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use christopherastone/distilgpt2-proofs with Docker Model Runner:
docker model run hf.co/christopherastone/distilgpt2-proofs
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (198bbf3f39d466b5790b492950f92e1c276bb610) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>fdd0388
-
Update README.md
Added widget-text metadata4e7b9f1
-
upload flax model
aa584d4 -
allow flax
2d5975f
-
Update README.md
7029aac -
Update README.md
edcc6a3 -
Update README.md
6ef4f66 -
Update README.md
79260f8 -
Update README.md
68c53e1 -
Update README.md
eec2898 -
Update README.md
90cb91f -
Create README.md
2d4a133 -
Create README.md
[DistilGPT2 English language model](https://huggingface.co/distilgpt2) fine-tuned on 29 years of mathematical proofs extracted from [arXiv.org](https://arxiv.org).414826a
-
Initial commit
Christopher A. Stone8361562 -
initial commit
588a198