Instructions to use Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice") model = AutoModelForTokenClassification.from_pretrained("Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56fd33641bf0368781a6d9a357ee6eea7161030cbf4e9ab2750d9ba882386604
- Size of remote file:
- 504 MB
- SHA256:
- a43c456c032a22f56dffd5f1a28ff0e335b58711c9b9278a16c42e4bed660101
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