Instructions to use microsoft/dit-base-finetuned-rvlcdip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/dit-base-finetuned-rvlcdip with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/dit-base-finetuned-rvlcdip") 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("microsoft/dit-base-finetuned-rvlcdip") model = AutoModelForImageClassification.from_pretrained("microsoft/dit-base-finetuned-rvlcdip") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d2ad3502c95b4f977397f18a9b9b84ae54443a92301251b8f3e881ca05ddc7d
- Size of remote file:
- 343 MB
- SHA256:
- 1b7a901642c36ec7e32de997683223faf02028624fb2e62a7e7e798a5dd1344e
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