Instructions to use nielsr/layoutlmv3-funsd-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/layoutlmv3-funsd-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nielsr/layoutlmv3-funsd-v2")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("nielsr/layoutlmv3-funsd-v2") model = AutoModelForTokenClassification.from_pretrained("nielsr/layoutlmv3-funsd-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc1460bc1b2329498337d9591476e309bdf5f88ee6decce08649688d1e9c1211
- Size of remote file:
- 501 MB
- SHA256:
- dd20b80c33bbcdaa0bf1ba3034dff5ea8a0a5de6bcfcfa29574f159569bce772
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