Instructions to use microsoft/markuplm-large-finetuned-websrc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/markuplm-large-finetuned-websrc with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="microsoft/markuplm-large-finetuned-websrc")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForQuestionAnswering processor = AutoProcessor.from_pretrained("microsoft/markuplm-large-finetuned-websrc") model = AutoModelForQuestionAnswering.from_pretrained("microsoft/markuplm-large-finetuned-websrc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/markuplm-large-finetuned-websrc: direct link, hf CLI and curl.
- Browser
- Download file 1.48 GB
-
https://huggingface.co/microsoft/markuplm-large-finetuned-websrc/resolve/12ecc71b77d24a5b3bed50f0dc00b1bf9cbdc32f/pytorch_model.bin
- Command line
-
hf download hf://microsoft/markuplm-large-finetuned-websrc@12ecc71b77d24a5b3bed50f0dc00b1bf9cbdc32f/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/markuplm-large-finetuned-websrc/resolve/12ecc71b77d24a5b3bed50f0dc00b1bf9cbdc32f/pytorch_model.bin
1.48 GB
- Xet hash:
- 62eae2cb28c8563b93c955e97719ecc89233b2d04ca2f0faea1d094fa58db174
- Size of remote file:
- 1.48 GB
- SHA256:
- 782147aae1f2b5661d029c173056a1408782072ad286d998656377094df2ef49
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.