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
- Xet hash:
- 258c349610a36f275d3f0437be8f6e99bb6637f2e857c6777968c3649bda9801
- Size of remote file:
- 6.63 kB
- SHA256:
- 4b793820b9df0998667deb6c8ce2dbb86b38221d5165c1844bc4971941b13f13
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