Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Woleek/bg-classif with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Woleek/bg-classif with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Woleek/bg-classif") 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("Woleek/bg-classif") model = AutoModelForImageClassification.from_pretrained("Woleek/bg-classif", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bfa42c059fd37c193bd4f59eb88c0d79d3f8e52c5ff268c86e27cc275c728fe
- Size of remote file:
- 343 MB
- SHA256:
- 6b19806ff6239529d9aabe437ae0e9a936bce95a080c95388102f36c105c1b1e
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