Instructions to use Sebastianpinar/lora2-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-40") 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/lora2-40") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 44
acaf6d9 -
Training in progress, epoch 40
726a544 -
Training in progress, epoch 36
3e351bc -
Training in progress, epoch 32
676116b -
Training in progress, epoch 30
d385fd2 -
Training in progress, epoch 26
a30cd33 -
Training in progress, epoch 22
6617ee6 -
Training in progress, epoch 20
13b078a -
Training in progress, epoch 16
91c7877 -
Training in progress, epoch 12
819f629 -
Training in progress, epoch 8
e0162a7 -
Training in progress, epoch 4
b2837c8 -
Training in progress, epoch 0
1799f71 -
initial commit
4b3c1e7