Instructions to use fimu-docproc-research/layoutlmv2-base-uncased-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fimu-docproc-research/layoutlmv2-base-uncased-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fimu-docproc-research/layoutlmv2-base-uncased-finetuned")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("fimu-docproc-research/layoutlmv2-base-uncased-finetuned") model = AutoModelForTokenClassification.from_pretrained("fimu-docproc-research/layoutlmv2-base-uncased-finetuned") - Notebooks
- Google Colab
- Kaggle
Fine-tuned LayoutLMv2 model on NER task using annotated invoices from the Intelligent Backoffice project. The usage outside our API is identical to the original LayoutLM.
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