Instructions to use Reshma27/Layout_LM_EntityExtractionFor_ProofOfAddress with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Reshma27/Layout_LM_EntityExtractionFor_ProofOfAddress with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Reshma27/Layout_LM_EntityExtractionFor_ProofOfAddress")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Reshma27/Layout_LM_EntityExtractionFor_ProofOfAddress") model = AutoModelForTokenClassification.from_pretrained("Reshma27/Layout_LM_EntityExtractionFor_ProofOfAddress") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
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