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ae3-tl

Object Detection
ONNX
Core ML
English
table-extraction
table-structure-recognition
document-ai
pdf
d-fine
Model card Files
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ae3-tl

Commit History

Yesterday

  1. Updated Readme.md

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  2. Update to Readme.md

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  3. Updated Readme.md

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2 days ago

  1. Upload README_ae3.md

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7 days ago

  1. Full extraction: SHA256SUMS

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  2. Full extraction: .gitignore

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  3. Remove __pycache__ from the upload

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  4. Full extraction: SHA256SUMS

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  5. Full extraction: THIRD_PARTY_NOTICES.md

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  6. Full extraction: example.py

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  7. Full extraction: USAGE.md

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  8. Full extraction: weights/ae3_tl.json

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  9. Full extraction: requirements.txt

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  10. Full extraction: extract.py

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  11. Add the extraction pipeline (src/ae3_tl)

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  12. macOS: state the M1 to M4 and macOS 13 range

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  13. macOS: add the Core ML package (fp32)

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  14. macOS: Core ML checksums

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  15. macOS: Core ML build (USAGE.md)

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  16. macOS: Core ML build (predict_mac.py)

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  17. macOS: Core ML build (README_mac.md)

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  18. macOS: CoreML required, no CPU fallback (USAGE.md)

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  19. macOS: CoreML required, no CPU fallback (example.py)

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  20. macOS: static batch shape and CoreML fallback (check_env.py)

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  21. macOS: static batch shape and CoreML fallback (example.py)

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  22. macOS: CoreML provider support (USAGE.md)

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  23. macOS: CoreML provider support (check_env.py)

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  24. macOS: CoreML provider support (example.py)

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  25. Fix: within 0.0022 on all six metrics

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8 days ago

  1. Chart label: image only, zero-shot

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  2. Label the Gemini row as image only

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  3. Add assets/density.png

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  4. Add assets/exact_match.png

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  5. Model card v3 with charts

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  6. Update USAGE.md

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  7. Update README.md

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  8. Remove NOTICE

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  9. Remove provenance.json

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  10. Add licenses/Apache-2.0.txt

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  11. Add licenses/table-transformer-MIT.txt

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  12. Add licenses/POTATR-MIT.txt

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  13. Add SHA256SUMS

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  14. Add SBOM.json

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  15. Add LICENSES_REPORT.md

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  16. Add THIRD_PARTY_NOTICES.md

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  17. Add ae3_tl.json

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  18. Add PROVENANCE.json

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  19. Add LICENSE.md

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  20. Add USAGE.md

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  21. Add README.md

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