Instructions to use li-jay-cs/gpt2-rlhf-rm-checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use li-jay-cs/gpt2-rlhf-rm-checkpoint with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("li-jay-cs/gpt2-rlhf-rm-checkpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5139b9909056b29c83cd2951bc68c6ba6c9c20fd8915371b1590e1d946f6a3d6
- Size of remote file:
- 575 MB
- SHA256:
- 1ca5c48cea44c4b9ec9eeb06a85ea100cfe26716c706dae51a304a1100602387
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.