Instructions to use RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("GPT2-Large") model = PeftModel.from_pretrained(base_model, "RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test: direct link, hf CLI and curl.
- Browser
- Download file 11.8 MB
-
https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test/resolve/refs%2Fpr%2F1/adapter_model.bin
- Command line
-
hf download hf://RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test@refs/pr/1/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2test/resolve/refs%2Fpr%2F1/adapter_model.bin
11.8 MB
- Xet hash:
- 3d02acd7a06eba1b66862483d6ff836413eac44670f0373c5a3a22e19f16c18d
- Size of remote file:
- 11.8 MB
- SHA256:
- 6de0359b74f5a1498c315548711888bfaa39bfb62111d5cdad76bec942180cfd
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