Instructions to use ghaith1997/layoutlmv3-documents-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghaith1997/layoutlmv3-documents-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghaith1997/layoutlmv3-documents-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("ghaith1997/layoutlmv3-documents-classification") model = AutoModelForSequenceClassification.from_pretrained("ghaith1997/layoutlmv3-documents-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 sha256:30b3b2b3027af609f606cce439d69f9ab7f08d38612ebcd8d9a03f7c4c9e893c
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size 503713112
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