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:
- f23443dbaf171f0524477096a11e3999704ece96463150a88150bb16a10b8f6a
- Size of remote file:
- 372 MB
- SHA256:
- 2e6d63ad1ba7f72cd453a1b8cc4253c58d744cebf7b8a296f71c3124b49d4129
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