Image Classification
Transformers
Safetensors
vit
image-classification, screenshots detection
Generated from Trainer
Instructions to use al-css/Screenshots_detection_to_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use al-css/Screenshots_detection_to_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="al-css/Screenshots_detection_to_classification") 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("al-css/Screenshots_detection_to_classification") model = AutoModelForImageClassification.from_pretrained("al-css/Screenshots_detection_to_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1e7cf8e7b63cdb6322261aa7bdd164c40fe6999df0e5aed435708cadce2376e
- Size of remote file:
- 343 MB
- SHA256:
- 91eb03484d046655fe18370c2c5d7ae71920714df38ed13a2ffbbbd083907649
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