Instructions to use microsoft/layoutlmv3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/layoutlmv3-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/layoutlmv3-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/layoutlmv3-large: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/microsoft/layoutlmv3-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/layoutlmv3-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/layoutlmv3-large/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 84334943c82371674400efd006695fd16d0439e4b51b163576693768b34d88c4
- Size of remote file:
- 1.42 GB
- SHA256:
- 747717fbcc0759de8f6f387d498974b9909f1591a6a473c47c15c39b43a195d2
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