Instructions to use ghaith1997/layoutlmv3-invoice-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghaith1997/layoutlmv3-invoice-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghaith1997/layoutlmv3-invoice-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("ghaith1997/layoutlmv3-invoice-classification") model = AutoModelForSequenceClassification.from_pretrained("ghaith1997/layoutlmv3-invoice-classification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:57dffd8af244dc2ab020a3cababc522b6a592c57b02de975ac0d3a4145b44c39
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size 503710032
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