Instructions to use RavindiG/layoutlmv3-document-classification-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RavindiG/layoutlmv3-document-classification-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RavindiG/layoutlmv3-document-classification-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("RavindiG/layoutlmv3-document-classification-v2") model = AutoModelForSequenceClassification.from_pretrained("RavindiG/layoutlmv3-document-classification-v2") - Notebooks
- Google Colab
- Kaggle