Instructions to use Ailyth/2_Labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ailyth/2_Labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Ailyth/2_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/2_Labels") model = AutoModelForImageClassification.from_pretrained("Ailyth/2_Labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 555258d4e6b286b7e538c1090cd08e9e23e5423868d7590687ce3aab97ca250d
- Size of remote file:
- 348 MB
- SHA256:
- 06fbd6d85bd24d4cd530cc94b50e92797ae5e97489227c1b62fb091525c87d9c
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