Instructions to use ishdes/layoutlmv3-ehr-scanned-document-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishdes/layoutlmv3-ehr-scanned-document-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ishdes/layoutlmv3-ehr-scanned-document-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("ishdes/layoutlmv3-ehr-scanned-document-classification") model = AutoModelForSequenceClassification.from_pretrained("ishdes/layoutlmv3-ehr-scanned-document-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcdf7fd90dff869da3dfd6137679dfb7635abde054d46f217e2c18a033ddd4ce
- Size of remote file:
- 504 MB
- SHA256:
- e60abb5a6d0340950ac6390b4938e9735468da85d89145c092ac42fd0341f5b8
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