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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28a017d3124c34ab578e5b0b43e99ee5d08bbe7c68742d1b046ba51456a8e53a
- Size of remote file:
- 511 MB
- SHA256:
- bf8b7882db23c58763acd876f50d04e3f291c8845febd3556f26b91f4b73f7c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.