Instructions to use AlekseyKorshuk/test_reward_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlekseyKorshuk/test_reward_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlekseyKorshuk/test_reward_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlekseyKorshuk/test_reward_model: direct link, hf CLI and curl.
- Browser
- Download file 551 MB
-
https://huggingface.co/AlekseyKorshuk/test_reward_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AlekseyKorshuk/test_reward_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AlekseyKorshuk/test_reward_model/resolve/main/pytorch_model.bin
551 MB
- Xet hash:
- 1c0dc1c428e8ff44dbf11499a9a09160759af0ab96f5d3a74a62fbceab0b58f2
- Size of remote file:
- 551 MB
- SHA256:
- 1c6dc8b95b70687c92426f53bbc7627ddb049047bd3349116e1089ee9be2ed4b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.