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")# pip install -U transformers accelerate # 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 tf_model.h5 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/tf_model.h5
- Command line
-
hf download hf://impira/layoutlm-document-qa@7743a4ee18f3ade6ba3cd846a897d7aaa062458f/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/impira/layoutlm-document-qa/resolve/7743a4ee18f3ade6ba3cd846a897d7aaa062458f/tf_model.h5
511 MB
- Xet hash:
- 192fa2ce30f927ac0aa32bc2544c9f67eaae5ce7c5d3697672ffd07932717561
- Size of remote file:
- 511 MB
- SHA256:
- 1b79d6d938ef00f3ef9666db0d12907855272a1c476145d1bd8440cfdb97e433
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