Instructions to use billyprodev/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use billyprodev/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="billyprodev/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("billyprodev/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("billyprodev/layoutlm-funsd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45cf54986e1eb147d1c0dcabffb425c3fdab222d18ba0eba3d4cb9dddd99efb9
- Size of remote file:
- 451 MB
- SHA256:
- 1153ebd09ab95a9cd65c68a2a87d4ac61194e258ee00aaa92803e6755e27b104
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.