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
Finetuned model availability for document parsing(OCR) or Key Information Extraction
#3 opened about 2 years ago
by
stray-light
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot
Custom train
1
#1 opened about 3 years ago
by
Ashv27