Instructions to use microsoft/dit-large-finetuned-rvlcdip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/dit-large-finetuned-rvlcdip with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/dit-large-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-large-finetuned-rvlcdip") model = AutoModelForImageClassification.from_pretrained("microsoft/dit-large-finetuned-rvlcdip", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f97d9ab111b6243ee2d1f0367b9cf3d82cb31ca0930ee07a83c4755a9b181a71
- Size of remote file:
- 1.21 GB
- SHA256:
- 819c39abe94292bfb9e2992a70053e49968b71563a352f156167b5f024499fac
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