Instructions to use impira/layoutlm-document-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impira/layoutlm-document-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="impira/layoutlm-document-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("impira/layoutlm-document-qa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("impira/layoutlm-document-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from impira/layoutlm-document-qa: direct link, hf CLI and curl.
- Browser
- Download file 511 MB
-
https://huggingface.co/impira/layoutlm-document-qa/resolve/7743a4ee18f3ade6ba3cd846a897d7aaa062458f/pytorch_model.bin
- Command line
-
hf download hf://impira/layoutlm-document-qa@7743a4ee18f3ade6ba3cd846a897d7aaa062458f/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/impira/layoutlm-document-qa/resolve/7743a4ee18f3ade6ba3cd846a897d7aaa062458f/pytorch_model.bin
511 MB
- Xet hash:
- 28a017d3124c34ab578e5b0b43e99ee5d08bbe7c68742d1b046ba51456a8e53a
- Size of remote file:
- 511 MB
- SHA256:
- bf8b7882db23c58763acd876f50d04e3f291c8845febd3556f26b91f4b73f7c9
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