Instructions to use Sharka/CIVQA_LayoutLMv3_EasyOCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharka/CIVQA_LayoutLMv3_EasyOCR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Sharka/CIVQA_LayoutLMv3_EasyOCR")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("Sharka/CIVQA_LayoutLMv3_EasyOCR") model = AutoModelForDocumentQuestionAnswering.from_pretrained("Sharka/CIVQA_LayoutLMv3_EasyOCR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ead2eb80a6efb29f52e295f144f757432ab13e7130e6099331e23914280e72f0
- Size of remote file:
- 5.77 MB
- SHA256:
- 37d6443ffce994679036c0248262aa8d4d96aca7b129ea2b96365849613ff64d
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