Text Generation
Transformers
PyTorch
English
gpt_neox
text generation
causal-lm
text-generation-inference
Instructions to use hoskinson-center/proofGPT-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hoskinson-center/proofGPT-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hoskinson-center/proofGPT-v0.1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("hoskinson-center/proofGPT-v0.1") model = AutoModelForCausalLM.from_pretrained("hoskinson-center/proofGPT-v0.1") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hoskinson-center/proofGPT-v0.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hoskinson-center/proofGPT-v0.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/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
docker model run hf.co/hoskinson-center/proofGPT-v0.1
- SGLang
How to use hoskinson-center/proofGPT-v0.1 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 "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 }' - Docker Model Runner
How to use hoskinson-center/proofGPT-v0.1 with Docker Model Runner:
docker model run hf.co/hoskinson-center/proofGPT-v0.1
| language: | |
| - en | |
| tags: | |
| - text generation | |
| - pytorch | |
| - causal-lm | |
| - gpt_neox | |
| license: mit | |
| datasets: | |
| - hoskinson-center/proof-pile | |
| # 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](https://huggingface.co/datasets/hoskinson-center/proof-pile). | |
| The model is initialized with [pythia-1.3b](https://huggingface.co/EleutherAI/pythia-1.3b) weights. ProofGPT-v0.1's Weights & Biases training log is viewable [here](https://wandb.ai/zhangir-azerbayev/math-lm/groups/1.3B%20preliminary_227qly9c/workspace?workspace=user-zhangir-azerbayev). | |
| Detailed evaluations coming soon :) | |
| **Note**: Commit `9695b51` updated the tokenizer to have bos, eos, and unk tokens. |