Instructions to use microsoft/markuplm-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/markuplm-base with Transformers:
# Load model directly from transformers import AutoProcessor, MarkupLMForPretraining processor = AutoProcessor.from_pretrained("microsoft/markuplm-base") model = MarkupLMForPretraining.from_pretrained("microsoft/markuplm-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7869c2478ec1db1a0e2a288628b739fe06df865374d9c001f5476bd3210c8d5b
- Size of remote file:
- 277 MB
- SHA256:
- 812da9c91ed2b8d807c15c610fad699893ae2e7163861a2675fc162bcd834185
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.