Instructions to use Sharka/CIVQA_DVQA_LayoutLMv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharka/CIVQA_DVQA_LayoutLMv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Sharka/CIVQA_DVQA_LayoutLMv3")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("Sharka/CIVQA_DVQA_LayoutLMv3") model = AutoModelForDocumentQuestionAnswering.from_pretrained("Sharka/CIVQA_DVQA_LayoutLMv3") - 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:c8851212dd23a362913e18ce0a316d3d000a15602628f58ab140a117eec0f3f0
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size 1117299168
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