Instructions to use TusharGoel/LiLT-Document-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TusharGoel/LiLT-Document-QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="TusharGoel/LiLT-Document-QA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("TusharGoel/LiLT-Document-QA") model = AutoModelForQuestionAnswering.from_pretrained("TusharGoel/LiLT-Document-QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TusharGoel/LiLT-Document-QA: direct link, hf CLI and curl.
- Browser
- Download file 521 MB
-
https://huggingface.co/TusharGoel/LiLT-Document-QA/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TusharGoel/LiLT-Document-QA/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TusharGoel/LiLT-Document-QA/resolve/main/pytorch_model.bin
521 MB
- Xet hash:
- a839ec69de26da7d93195f36278e7e40581a588edb88412a2190d2a43f6c721e
- Size of remote file:
- 521 MB
- SHA256:
- 3c690371b5208f040b164f9fcce351b3e69970c2232965a1002afe6b486aa37d
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