Instructions to use Sebastianpinar/lora2-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-13") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Sebastianpinar/lora2-13") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 34
da63827 -
Training in progress, epoch 29
964230b -
Training in progress, epoch 24
fd3bb0b -
Training in progress, epoch 20
05b31c6 -
Training in progress, epoch 14
d6a9690 -
Training in progress, epoch 9
ec9d66a -
Training in progress, epoch 5
1ec26d7 -
Training in progress, epoch 0
92a3b42 -
initial commit
33569e1