Instructions to use li-jay-cs/test2-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/test2-rlhf-rm-checkpoint with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("li-jay-cs/test2-rlhf-rm-checkpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from li-jay-cs/test2-rlhf-rm-checkpoint: direct link, hf CLI and curl.
- Browser
- Download file 232 Bytes
-
https://huggingface.co/li-jay-cs/test2-rlhf-rm-checkpoint/resolve/main/config.json
- Command line
-
hf download hf://li-jay-cs/test2-rlhf-rm-checkpoint/config.json
-
curl -L -o config.json https://huggingface.co/li-jay-cs/test2-rlhf-rm-checkpoint/resolve/main/config.json
232 Bytes
| { | |
| "architectures": [ | |
| "GPTRewardModel" | |
| ], | |
| "model_path": "li-jay-cs/gptj-supervised-summarize-checkpoint", | |
| "model_type": "reward", | |
| "tokenizer_id": "gpt2", | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.35.2" | |
| } | |