Instructions to use edonath/layoutlmv3-financial-document-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edonath/layoutlmv3-financial-document-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edonath/layoutlmv3-financial-document-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("edonath/layoutlmv3-financial-document-classification") model = AutoModelForSequenceClassification.from_pretrained("edonath/layoutlmv3-financial-document-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:3084b12abe90f0e54d1db690c2e96f2c95aa081175f9af7bee295e43b0d1fef7
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size 503716188
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