Instructions to use Ailyth/3_Labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ailyth/3_Labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Ailyth/3_Labels") 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("Ailyth/3_Labels") model = AutoModelForImageClassification.from_pretrained("Ailyth/3_Labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4af85988b6f0bcfff56227755d42daf3fbe00a3a0b266708374c60557ba4cb8f
- Size of remote file:
- 348 MB
- SHA256:
- cedc07f507204b184b2dba718e9759fec6963b5bb2716f88bb60f83d5f7b43c4
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