Instructions to use bikaandrei/layoutlmv1-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bikaandrei/layoutlmv1-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bikaandrei/layoutlmv1-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bikaandrei/layoutlmv1-funsd") model = AutoModelForTokenClassification.from_pretrained("bikaandrei/layoutlmv1-funsd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97484200bb32bf5e84a6f2832126f3a19bf100137ac5d197297991b6277372b7
- Size of remote file:
- 5.78 kB
- SHA256:
- e55c30eb593752a34b71a9b6927bec25476a7d92d30a3272e3bae80a49dd9144
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