This package contains tools to train deep learning models using attribution priors. Through attribution priors, practitioners can constraint models to behave more intuitively on a wide variety of tasks. For usage guidelines, see the GitHub repo. For more details about how to use attribution priors, see the arXiv paper.
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Release files for attributionpriors 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| attributionpriors-0.1.3.tar.gz | 15.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| attributionpriors-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 30.6 kB
Release files / attributionpriors-0.1.3.tar.gz
| Download URL | attributionpriors-0.1.3.tar.gz |
|---|---|
| Size | 15.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8
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Release files / attributionpriors-0.1.3-py3-none-any.whl
| Download URL | attributionpriors-0.1.3-py3-none-any.whl |
|---|---|
| Size | 15.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8
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