Instructions to use ekazakos/grove with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ekazakos/grove with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ekazakos/grove", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signaturee5a5544 -
Update README.md
Verified signatured2aa8cc
-
Improve model card: Add library name, project page, abstract, and news section (#2)
Verified signature- Improve model card: Add library name, project page, abstract, and news section (a4593ee2eb4374388168267c1f7ee67966b8a500) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>404c4a6
-
Add pipeline tag (#1)
Verified signature- Add pipeline tag (5d53d0007ee190b1cf95e79322c2fc3f67b3a0ef) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>7d62092
-
Update README.md
Verified signature5eea839 -
Update README.md
Verified signature3d4d234 -
Update README.md
Verified signatureb8e6921 -
Update README.md
Verified signature18be61f -
Create README.md
Verified signaturedfb808b -
Upload artifacts
Verified signature8e1d2de -
initial commit
Verified signaturedf2483c