Instructions to use RajuEEE/RewardModelForQuestionAnswering_GPT2_RevisedData with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RajuEEE/RewardModelForQuestionAnswering_GPT2_RevisedData 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_RevisedData") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from RajuEEE/RewardModelForQuestionAnswering_GPT2_RevisedData: direct link, hf CLI and curl.
- Browser
- Download file 99 Bytes
-
https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_RevisedData/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://RajuEEE/RewardModelForQuestionAnswering_GPT2_RevisedData/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/RajuEEE/RewardModelForQuestionAnswering_GPT2_RevisedData/resolve/main/special_tokens_map.json
99 Bytes
| { | |
| "bos_token": "<|endoftext|>", | |
| "eos_token": "<|endoftext|>", | |
| "unk_token": "<|endoftext|>" | |
| } | |