Instructions to use Sebastianpinar/lora2-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-10") 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/lora2-10") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 37
8f6d790 -
Training in progress, epoch 32
4398c51 -
Training in progress, epoch 26
d9b8ada -
Training in progress, epoch 20
00afda6 -
Training in progress, epoch 16
f92b521 -
Training in progress, epoch 10
2561b8c -
Training in progress, epoch 5
65510ab -
Training in progress, epoch 0
3c67fb6 -
initial commit
cf88d88