Instructions to use 02shanky/test_model_graphics_classification_ADAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 02shanky/test_model_graphics_classification_ADAM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="02shanky/test_model_graphics_classification_ADAM") 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("02shanky/test_model_graphics_classification_ADAM") model = AutoModelForImageClassification.from_pretrained("02shanky/test_model_graphics_classification_ADAM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ff1fdcfd23d5f85ca6c026a4a61cebf654b15eaff8b83570677c6e632869b2
- Size of remote file:
- 343 MB
- SHA256:
- eaa587990eeca4069a229154af0643bb0b204f936f3852f70105ecf469eef2ae
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