Instructions to use Dhineshk/TestDocumentQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dhineshk/TestDocumentQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Dhineshk/TestDocumentQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("Dhineshk/TestDocumentQuestionAnswering") model = AutoModelForDocumentQuestionAnswering.from_pretrained("Dhineshk/TestDocumentQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:500f0a4ceddc3182b8352234dd4ee19dc458ccc2834aeed1831571e674b6edb1
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size 802053752
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