Instructions to use microsoft/layoutlmv3-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/layoutlmv3-base-chinese with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/layoutlmv3-base-chinese", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1751731967d76fca852ebbabe72772402dc53a92c0e6a2bbd603875c5dfb0ce9
- Size of remote file:
- 1.11 GB
- SHA256:
- c4201006336797c5b9d851fc9a36e2e838e321e43b662a204c51cdbdc3783f21
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.