Instructions to use amaye15/SwinV2-Base-Document-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amaye15/SwinV2-Base-Document-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amaye15/SwinV2-Base-Document-Classifier") 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("amaye15/SwinV2-Base-Document-Classifier") model = AutoModelForImageClassification.from_pretrained("amaye15/SwinV2-Base-Document-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 777cf04d9fdd26dbd2d073703a20f9e03221a203d739dc789e5cf7ae6fdeb1cd
- Size of remote file:
- 5.24 kB
- SHA256:
- 9b39b2c4ea4fcb1b23ec1ec99a0fee7dfb4a85ab083cdd82698c4e2d44a09eee
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