Instructions to use Rodr16020/detr_handwriten_cursive_text_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rodr16020/detr_handwriten_cursive_text_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Rodr16020/detr_handwriten_cursive_text_detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Rodr16020/detr_handwriten_cursive_text_detection") model = AutoModelForObjectDetection.from_pretrained("Rodr16020/detr_handwriten_cursive_text_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Version 3
Verified signatureNew finetuning using more examplese91e7f4 -
Version 3
Verified signatureNew finetuning using more examples96f04b3
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Finetuned version Fuli_V6. More examples and positions were added. In total 620 samples
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Finetuned version Fuli_V6. More examples and positions were added. In total 620 samples
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Finetuned version Fuli_V6. More examples and positions were added. In total 620 samples
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Update README.md
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Finetuned V2 with more and curated data
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Finetuned V2 with more and curated data
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First Version - Akivili V1
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First Version - Akivili V1
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initial commit
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