Instructions to use Aalaa/Fine_tuned_Vit_trash_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aalaa/Fine_tuned_Vit_trash_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Aalaa/Fine_tuned_Vit_trash_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Aalaa/Fine_tuned_Vit_trash_classification") model = AutoModelForImageClassification.from_pretrained("Aalaa/Fine_tuned_Vit_trash_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Aalaa/Fine_tuned_Vit_trash_classification: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/Aalaa/Fine_tuned_Vit_trash_classification/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://Aalaa/Fine_tuned_Vit_trash_classification@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Aalaa/Fine_tuned_Vit_trash_classification/resolve/refs%2Fpr%2F1/optimizer.pt
687 MB
- Xet hash:
- 1d4da269424b85e225d942af92d2f753b1965238b4ad665deaf12ac27515b5af
- Size of remote file:
- 687 MB
- SHA256:
- e03ceb6e24b0b5cf000f1ef927bbf50eba06f9a882e4bed352ea5410017500e3
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