Instructions to use Midas2002/Slick-101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Midas2002/Slick-101 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Midas2002/Slick-101") 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("Midas2002/Slick-101") model = AutoModelForImageClassification.from_pretrained("Midas2002/Slick-101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 929955d5441a6f06bec5a01074844cfd2a97cf5dfb27f887264f55ce5c8e58ee
- Size of remote file:
- 5.78 kB
- SHA256:
- 5d959e1af8dfbb3d1dfa85958bc99b1554ab5094a0cf3f9d898f34365a6b5efa
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