Instructions to use itsmefaiz/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itsmefaiz/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="itsmefaiz/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("itsmefaiz/image_classification") model = AutoModelForImageClassification.from_pretrained("itsmefaiz/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52046b36923b5f802aacbc707da87851fc314d714c6e3b0b654eecb00bfdff19
- Size of remote file:
- 343 MB
- SHA256:
- 97f40ef1a3e0430dc08eb6c8588cc567f93bcec2e40361fb040fadb4de6b2424
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