Instructions to use shivank21/llama_dpo_reward_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shivank21/llama_dpo_reward_full with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shivank21/llama_dpo_reward_full", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3a2d103758c9f910ce5f8798408116bbf61f04d55820442c5442ab712956154
- Size of remote file:
- 721 MB
- SHA256:
- b3c693f501fd73ed310340891eebc7e10ba414383cd6f32a128793bd0a258230
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