Text Classification
PEFT
Safetensors
rag-gym
retrieval-augmented-generation
agent
lora
process-supervision
reward-model
Instructions to use RAG-Gym/ReSearch-HotpotQA-PRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RAG-Gym/ReSearch-HotpotQA-PRM with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "RAG-Gym/ReSearch-HotpotQA-PRM") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from RAG-Gym/ReSearch-HotpotQA-PRM: direct link, hf CLI and curl.
- Browser
- Download file 604 MB
-
https://huggingface.co/RAG-Gym/ReSearch-HotpotQA-PRM/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://RAG-Gym/ReSearch-HotpotQA-PRM/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/RAG-Gym/ReSearch-HotpotQA-PRM/resolve/main/adapter_model.safetensors
604 MB
- Xet hash:
- 6cd4a1ecc93b26ee7d7247743c747c45823f20432d8d24ee710ca34ec6dda6a3
- Size of remote file:
- 604 MB
- SHA256:
- 81480686afea10125afbe3216fbf10b5039607b7b537b46861dc9a02c14fc0a8
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