Transformers
Safetensors
English
deberta-v2
reward_model
reward-model
RLHF
evaluation
llm
instruction
reranking
Instructions to use mightbe/Better-PairRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mightbe/Better-PairRM with Transformers:
# Load model directly from transformers import AutoTokenizer, DebertaV2PairRM tokenizer = AutoTokenizer.from_pretrained("mightbe/Better-PairRM") model = DebertaV2PairRM.from_pretrained("mightbe/Better-PairRM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b7af49609223293d9e19883b90d4e7e6fe3edb819f8832c2dd96c4f8574551c
- Size of remote file:
- 4.66 kB
- SHA256:
- a076d677e06637d318f97a7dad62d7d53a64a87014538e9d7a2afc0efac6d170
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