Instructions to use Bochkov/bvv241-2-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bochkov/bvv241-2-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Bochkov/bvv241-2-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Bochkov/bvv241-2-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signaturefec177c
-
Update README.md
Verified signature09142b1
-
Update README.md
Verified signature901e82d -
Improve model card: Add metadata, paper and GitHub links (#1)
Verified signature- Improve model card: Add metadata, paper and GitHub links (90f4525ab2db7080ab3b186c9a8a7486544d4659) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>93e7d5f
-
Update README.md
Verified signature811be45
-
Update README.md
Verified signaturef7427a6
-
Update README.md
Verified signaturee1125fe
-
Update README.md
Verified signature0cef3dd -
Update README.md
Verified signatureaa9a8f5 -
Update README.md
Verified signature0af918a -
Update README.md
Verified signature0943dae -
Update README.md
Verified signature6e34c48 -
Update README.md
Verified signature83d26d0 -
Create README.md
Verified signature5156d08
-
Upload folder using huggingface_hub
Verified signature2727b44 -
initial commit
Verified signature83cc112