Instructions to use RajuEEE/RewardModelForQuestionAnswering_GPT2_Method1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RajuEEE/RewardModelForQuestionAnswering_GPT2_Method1 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_Method1") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from RajuEEE/RewardModelForQuestionAnswering_GPT2_Method1: direct link, hf CLI and curl.
- Browser
- Download file 11.8 MB
-
https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_Method1/resolve/main/adapter_model.bin
- Command line
-
hf download hf://RajuEEE/RewardModelForQuestionAnswering_GPT2_Method1/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_Method1/resolve/main/adapter_model.bin
11.8 MB
- Xet hash:
- 1319b272235eee2007082a87283bcdaa9daf31afcc61fd925d9c68df091dca41
- Size of remote file:
- 11.8 MB
- SHA256:
- b7b2ef5d26197f467faddbed2ed0992ab8d6077b20c06104792c8e5ba4f91bf7
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