Instructions to use paddeh/is-it-max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paddeh/is-it-max with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="paddeh/is-it-max") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("paddeh/is-it-max") model = AutoModelForImageClassification.from_pretrained("paddeh/is-it-max", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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build: add .gitignore
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docs: add contents to README.md
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model: retrained with more images of max in nature
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Create README.md
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Initial commit of the is-it-max model, based on training on 2025-02-20
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initial commit
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