Instructions to use Bochkov/bvv241-max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bochkov/bvv241-max with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Bochkov/bvv241-max")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Bochkov/bvv241-max", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signatureaea7c6f
-
Update README.md
Verified signature4f1240a -
Update README.md
Verified signature8921471 -
Improve model card: Add metadata and GitHub link (#1)
Verified signature- Improve model card: Add metadata and GitHub link (12eb488f09552901b0a5c7bf7fa9523f4311c9f0) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>f60d3f0
-
Update README.md
Verified signature2fe5112
-
Update README.md
Verified signature6de96d0
-
Update README.md
Verified signatureb2ddd52
-
Update README.md
Verified signature9021e1f -
Update README.md
Verified signature2b3556f -
Create README.md
Verified signature6e67568
-
Upload folder using huggingface_hub
Verified signatureaf565c7 -
initial commit
Verified signaturecd8d560