Instructions to use llm-blender/PairRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llm-blender/PairRM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="llm-blender/PairRM")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llm-blender/PairRM", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use llm-blender/PairRM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "llm-blender/PairRM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "llm-blender/PairRM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/llm-blender/PairRM
- SGLang
How to use llm-blender/PairRM 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 "llm-blender/PairRM" \ --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": "llm-blender/PairRM", "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 "llm-blender/PairRM" \ --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": "llm-blender/PairRM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use llm-blender/PairRM with Docker Model Runner:
docker model run hf.co/llm-blender/PairRM
Run model with transformers?
Hello, very nice work with PairRM - it looks quite handy for quality control of preference datasets :)
I was wondering if it's possible to run the model natively in transformers instead of requiring the llmblender library?
Thank you for the question. However, PairRM contains some self-dedesigend layers and it's kind of diffucult to make it compatible with existing codes of transformer library.
Besides, llm-blender also designs some simple interface functions so that PairRM can be properly used, such as compare(), compare_conversations, best_of_n_generate, etc. And integrating with transformers can't provide these inferfaces.
We also have set the minimum packages requirements to install llm-blender package, you can check the setup.py in our Github repo. Therefore, I think installing llm-blender won't cause too many package conflicts in the python environment.
If there are some other scenarios where installing llm-blender will cause conflicts, you can notice us, and see if we can resolve it.