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
Fine-tune and using in commercial
#15
by nam-leduc - opened
Hi everyone, thank you so much for contributing a very nice repo to the community.
I see in your license that MIT, so now my company wants to use this model in production.
Will we be allowed to do that?
Additional, we want to be able to fine-tune the model.
Do you have any resources about how to fine-tune "impira/layoutlm-document-qa"?
This is my first time working with hugging face and AI for production.
I look forward to hearing from you.
Thank you!
Hi did you get your answer? My company also want to use it. But only layoutlm v1 is open source but the rest of them are not.
I am not sure about this model.
Care to put in some feedback?