Instructions to use Siddanna/transparent-tube-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siddanna/transparent-tube-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Siddanna/transparent-tube-classifier") 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("Siddanna/transparent-tube-classifier") model = AutoModelForImageClassification.from_pretrained("Siddanna/transparent-tube-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a8c4fdd71b4978b2b97717440683031e33fa46f7072ec2c289943f1157ec23c
- Size of remote file:
- 5.33 kB
- SHA256:
- 1ee847a252249e1a7785bd1ac55dc65f335ea4900f8e3dc34c9db45c3eb701db
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