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:
- acf7bf10b029b9ac3b0e662f4b7682cc632850837cfa23db28bc8634f6627db3
- Size of remote file:
- 343 MB
- SHA256:
- fc3d6081d8359a78d92e5dc91d8b1e21c314d5745d28856a45b242e57d9863db
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