Instructions to use impira/layoutlm-document-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impira/layoutlm-document-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="impira/layoutlm-document-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("impira/layoutlm-document-classifier") model = AutoModelForSequenceClassification.from_pretrained("impira/layoutlm-document-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from impira/layoutlm-document-classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.38 kB
-
https://huggingface.co/impira/layoutlm-document-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://impira/layoutlm-document-classifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/impira/layoutlm-document-classifier/resolve/main/training_args.bin
1.38 kB
- Xet hash:
- 5a3672139b75a957dbd15fdce58fdfa353c434e25ac0543394454b7825e78828
- Size of remote file:
- 1.38 kB
- SHA256:
- ca34845dbb6dfad761d6808888081e3fcef65f6ff80b4f31a4b4f517590cfdad
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