Instructions to use Sebastianpinar/lora-42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora-42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora-42") 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-42") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora-42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fe76feeca7cdacc5c4e195c18b28177c4eb8efa9d280125b3eaff9684b3c981
- Size of remote file:
- 4.03 kB
- SHA256:
- d0b6c9d439223baea029dcfbb73b29f041a5b52a2a5dc3428911eb143f8a93d5
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