Text Generation
PEFT
Safetensors
rag-gym
retrieval-augmented-generation
agent
lora
process-supervision
search-agent
conversational
Instructions to use RAG-Gym/CoT-HotpotQA-DPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RAG-Gym/CoT-HotpotQA-DPO with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "RAG-Gym/CoT-HotpotQA-DPO") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RAG-Gym/CoT-HotpotQA-DPO: direct link, hf CLI and curl.
- Browser
- Download file 6.39 kB
-
https://huggingface.co/RAG-Gym/CoT-HotpotQA-DPO/resolve/main/training_args.bin
- Command line
-
hf download hf://RAG-Gym/CoT-HotpotQA-DPO/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RAG-Gym/CoT-HotpotQA-DPO/resolve/main/training_args.bin
6.39 kB
- Xet hash:
- 2a7eb88d6c4e33aa1d6a58597f3b9032533cce1b7e1bd77582620b07fbe309c7
- Size of remote file:
- 6.39 kB
- SHA256:
- f9f80652c885def60a436631703f43af5b2cc31e437b5596a969c94d930070d8
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