Instructions to use TirthDesai/Image-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TirthDesai/Image-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TirthDesai/Image-Classification") 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("TirthDesai/Image-Classification") model = AutoModelForImageClassification.from_pretrained("TirthDesai/Image-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 639299c4b7721d308a36a2e4a42203c0146e2e0283bdea689e6dca7417b76e40
- Size of remote file:
- 343 MB
- SHA256:
- 887ae99d6a7b0f43ec754157d0580065e8ddfb4734e329edd504350659323353
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