Instructions to use prithivMLmods/Traffic-Density-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Traffic-Density-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Traffic-Density-Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Traffic-Density-Classification") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Traffic-Density-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 560c7cfbac779a72125872851622031133cdafe113d33271336d597cfbef5ef3
- Size of remote file:
- 5.3 kB
- SHA256:
- f2b6e4446124f763a6e830979bd60cfae2d0dd6039989c0d2b96713f66a84def
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