Token Classification
Transformers
PyTorch
TensorBoard
layoutlmv3
Generated from Trainer
Eval Results (legacy)
Instructions to use jinhybr/OCR-LayoutLMv3-Invoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinhybr/OCR-LayoutLMv3-Invoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jinhybr/OCR-LayoutLMv3-Invoice")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("jinhybr/OCR-LayoutLMv3-Invoice") model = AutoModelForTokenClassification.from_pretrained("jinhybr/OCR-LayoutLMv3-Invoice") - 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 sha256:658724ecf8c9ded6744cdcfc944139190f85cdc7c46ae84dd7daa5b5a52a8e6b
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size 503780784
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