Instructions to use Sebastianpinar/lora2-36 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-36 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-36") 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/lora2-36") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-36", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 46
503265f -
Training in progress, epoch 41
c395039 -
Training in progress, epoch 38
8ef79ce -
Training in progress, epoch 34
2190525 -
Training in progress, epoch 30
818298b -
Training in progress, epoch 26
7f75912 -
Training in progress, epoch 24
a6b19f6 -
Training in progress, epoch 20
ad7a7b5 -
Training in progress, epoch 16
26e2782 -
Training in progress, epoch 12
44f8666 -
Training in progress, epoch 8
492df98 -
Training in progress, epoch 4
8bf5646 -
Training in progress, epoch 0
0865df0 -
initial commit
3c2a428