Instructions to use RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2 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_Method2") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2: direct link, hf CLI and curl.
- Browser
- Download file 11.8 MB
-
https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2/resolve/main/adapter_model.bin
- Command line
-
hf download hf://RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_Method2/resolve/main/adapter_model.bin
11.8 MB
- Xet hash:
- d7b700e974a20104cb3739e88a69264da652e2b49ec3c5dc4abf41119b0d67d5
- Size of remote file:
- 11.8 MB
- SHA256:
- d130478b6f35880418f1ac0c15b567541d77495163d2ad3e91ea8604725505af
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