Instructions to use ProtoFaze/layoutlmv2_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProtoFaze/layoutlmv2_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ProtoFaze/layoutlmv2_output")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("ProtoFaze/layoutlmv2_output") model = AutoModelForTokenClassification.from_pretrained("ProtoFaze/layoutlmv2_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acc9fae28a9982d5f739ec2ae74a0710be79569612b62b3b70d4a0706d7ab5e1
- Size of remote file:
- 5.65 kB
- SHA256:
- 7ec9cab58bea78eff5719c45da43340ffcee6f1ecb1456bd8d36fd9957ca192f
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