Instructions to use Mahmoud7/LayoutLMv3_diff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud7/LayoutLMv3_diff with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mahmoud7/LayoutLMv3_diff")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Mahmoud7/LayoutLMv3_diff") model = AutoModelForTokenClassification.from_pretrained("Mahmoud7/LayoutLMv3_diff", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mahmoud7/LayoutLMv3_diff: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/Mahmoud7/LayoutLMv3_diff/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud7/LayoutLMv3_diff/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud7/LayoutLMv3_diff/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- 7fb15ca2a241b3deac16c674df1f5a388de59ab474c246499ee0736dbf6bc533
- Size of remote file:
- 504 MB
- SHA256:
- b4b52ae9bc71d954eeaef20570d163219cfae9f78e7e7af444e4c22203952457
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.