Instructions to use brain-bzh/reve-positions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brain-bzh/reve-positions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="brain-bzh/reve-positions", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("brain-bzh/reve-positions", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers import PretrainedConfig | |
| class RevePositionBankConfig(PretrainedConfig): | |
| model_type = "reve-position-bank" | |
| def __init__(self, position_names: list[str] = [], **kwargs): | |
| super().__init__(**kwargs) | |
| self.position_names = position_names | |