Instructions to use dongboklee/gPRM-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dongboklee/gPRM-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dongboklee/gPRM-8B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dongboklee/gPRM-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dongboklee/gPRM-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dongboklee/gPRM-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dongboklee/gPRM-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/dongboklee/gPRM-8B
- SGLang
How to use dongboklee/gPRM-8B 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 "dongboklee/gPRM-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dongboklee/gPRM-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "dongboklee/gPRM-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dongboklee/gPRM-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use dongboklee/gPRM-8B with Docker Model Runner:
docker model run hf.co/dongboklee/gPRM-8B
Improve model card: Add HF paper link and fix code snippet
#1
by nielsr HF Staff - opened
Hi! Great work on this model and the detailed model card. This PR introduces a couple of improvements:
- Adds the direct Hugging Face paper link for "Rethinking Reward Models for Multi-Domain Test-Time Scaling" for improved discoverability, while retaining the arXiv link.
- Fixes logical errors in the "Direct Use" code snippet related to prompt formatting (
stepsvariable definition andprefixassignment) and how the model's output scores are accessed. The updated snippet should now run without errors, ensuring users can correctly try out the model.
Thanks for sharing your work with the community!