Instructions to use sudheer997/lambdaV3-FUNSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sudheer997/lambdaV3-FUNSD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sudheer997/lambdaV3-FUNSD")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("sudheer997/lambdaV3-FUNSD") model = AutoModelForTokenClassification.from_pretrained("sudheer997/lambdaV3-FUNSD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c993cdc243c877966a0f3a5eaec8efa861a38bf9235596a6c58f200dfa18e01b
- Size of remote file:
- 501 MB
- SHA256:
- 9fa942e9f59d123635237cfff30fd1766597d0e0811b1680a3d8d7b2d52f2eac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.