Instructions to use pddq/layoutlmv3-medical-document-classifier-10cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pddq/layoutlmv3-medical-document-classifier-10cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pddq/layoutlmv3-medical-document-classifier-10cls")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("pddq/layoutlmv3-medical-document-classifier-10cls") model = AutoModelForSequenceClassification.from_pretrained("pddq/layoutlmv3-medical-document-classifier-10cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot