Instructions to use jordyvl/LayoutLMv3_RVL-CDIP_NK100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jordyvl/LayoutLMv3_RVL-CDIP_NK100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jordyvl/LayoutLMv3_RVL-CDIP_NK100")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("jordyvl/LayoutLMv3_RVL-CDIP_NK100") model = AutoModelForSequenceClassification.from_pretrained("jordyvl/LayoutLMv3_RVL-CDIP_NK100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot