Instructions to use Prem11100/layoutlmv3-financial-document-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prem11100/layoutlmv3-financial-document-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prem11100/layoutlmv3-financial-document-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Prem11100/layoutlmv3-financial-document-classification") model = AutoModelForSequenceClassification.from_pretrained("Prem11100/layoutlmv3-financial-document-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe2ba32d047fa26e9d8d0501a48b8f075381bb98a4301a86d976aec86fc9d26a
- Size of remote file:
- 504 MB
- SHA256:
- 3efca23915815bea33a15e6bb768e6d2ff6106c30b25d9382f26044683500e4b
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