Instructions to use microsoft/layoutlmv3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/layoutlmv3-base with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/layoutlmv3-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Is the pretrained model cased or uncased?
#6
by nediaz2 - opened
Seems like the tokenizer is not doing lower case on the input string, so I assume the model is cased?
The vocab is cased indeed. LayoutLMv3's tokenizer is based on BPE (byte-pair encoding), similar to RoBERTa.
