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
Not support for Chinese,What a pity!
I try some Chinese samples, this model can not support Chinese QA, What a pity! Can it retrain for Chinese?
Hi @luojiluoji , the base model that this is fine tuned on (LayoutLM) is English-only. Microsoft has a multi-lingual version called LayoutXLM, but unfortunately it's licensed with CC BY-NC-SA 4.0, preventing commercial use: https://github.com/microsoft/unilm/tree/master/layoutxlm. If that's not an issue, you could definitely fine tune it over a similar dataset and use it!
Hi @luojiluoji , the base model that this is fine tuned on (LayoutLM) is English-only. Microsoft has a multi-lingual version called LayoutXLM, but unfortunately it's licensed with CC BY-NC-SA 4.0, preventing commercial use: https://github.com/microsoft/unilm/tree/master/layoutxlm. If that's not an issue, you could definitely fine tune it over a similar dataset and use it!
Oh,thanks,I will try it。