Instructions to use Maaz66/layoutlmv3-financial-document-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maaz66/layoutlmv3-financial-document-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Maaz66/layoutlmv3-financial-document-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Maaz66/layoutlmv3-financial-document-classification") model = AutoModelForSequenceClassification.from_pretrained("Maaz66/layoutlmv3-financial-document-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ace8cc8da8f3ab1eafd9c48f77c6c0ff9e1cd63ec3b8241342f0bbfb9f6449d6
- Size of remote file:
- 504 MB
- SHA256:
- c00b9728a6caa90c3beb0115bf13986c83cd5d9a00dd7a55041432f0f8d67ebc
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