Instructions to use Mahmoud7/LayoutLMv3_diff_nu2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud7/LayoutLMv3_diff_nu2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mahmoud7/LayoutLMv3_diff_nu2")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Mahmoud7/LayoutLMv3_diff_nu2") model = AutoModelForTokenClassification.from_pretrained("Mahmoud7/LayoutLMv3_diff_nu2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c924d6cdb4e9c31712387cc0defaf1c11ecce36ae1c5d5b2a77861235eb8a3c
- Size of remote file:
- 504 MB
- SHA256:
- f69903aa634afb0ff9c6795a2b5690937d31e3f5baa1f06fb82e345593bac2f1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.