Instructions to use Sebastianpinar/lora-59 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora-59 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora-59") 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/lora-59") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora-59") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5161ec9937fa7f2f5c735b1200a3269c209c7a70022e20e37b337473c8dea65d
- Size of remote file:
- 347 MB
- SHA256:
- ad51611ea09d16a8f5038fb73e4311743b48ac5a3a204b575f950ce0ac68a6fd
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