Instructions to use Sebastianpinar/lora2-82 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-82 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-82") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Sebastianpinar/lora2-82") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-82", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d9e1f1677d45970a7aa810b644db609662807f05d441c0a25f82b98ba57d250
- Size of remote file:
- 4.09 kB
- SHA256:
- 139b98597517d6207085406ab51586c13aad4c9825679bb42edb522da83b545f
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