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")# pip install -U transformers accelerate # 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
Add MIT license metadata
#2
by muhammadsaeed1 HF Staff - opened
License confirmed by Tengchao Lv (Microsoft Research, DiT co-author) by email on 2026-10-09: the MIT license of microsoft/unilm also applies to the released DiT weights.
julien-c changed pull request status to merged