Instructions to use oliversssf2/distilbert-base-uncased-rm-helpful with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oliversssf2/distilbert-base-uncased-rm-helpful with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("oliversssf2/distilbert-base-uncased-rm-helpful", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 197 Bytes
aa3e1bf | 1 2 3 4 5 6 | Load the reward model with the following code
```python
from reward_modelling.reward_model import RewardModel
rm = RewardModel.from_pretrained('oliversssf2/distilbert-base-uncased-rm-helpful')
``` |