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1.0.2 vespa_effect-1.0.2-py3-none-any.whl

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Project: vespa-effect
Version: 1.0.2
Filename: vespa_effect-1.0.2-py3-none-any.whl
Download: [link]
Size: 3419895
MD5: ad7b9b09e8df8536f41cc8c6288d4207
SHA256: c5b43678a120ea3987175427ea8dd8ff407942c8d0d1e2b1bf19f3ed28cc06b6
Uploaded: 2023-03-16 23:13:52 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: vespa-effect
Version: 1.0.2
Summary: Predictor for single-amino acid variant effects in protein sequences (https://doi.org/10.1007/s00439-021-02411-y)
Author: Tobias O
Author-Email: tobias.olenyi[at]tum.de
Home-Page: https://github.com/Rostlab/VESPA
Project-Url: Repository, https://github.com/Rostlab/VESPA
License: AGPL-3.0-or-later
Keywords: Embeddings,Protein-Sequences,Machine-Learning,Mutation-Effect
Classifier: License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.8,<3.11
Requires-Dist: biopython (<2.0,>=1.79)
Requires-Dist: h5py (<4.0.0,>=3.4.0)
Requires-Dist: numpy (<2.0.0,>=1.21.2)
Requires-Dist: pyfaidx (<0.7.0,>=0.6.2)
Requires-Dist: scikit-learn (<2.0.0,>=1.2.2)
Requires-Dist: sentencepiece (<0.2.0,>=0.1.96)
Requires-Dist: torch (<2.0.0,>=1.9.0)
Requires-Dist: tqdm (<5.0.0,>=4.62.2)
Requires-Dist: transformers (<5.0.0,>=4.10.2)
Description-Content-Type: text/markdown
[Description omitted; length: 15854 characters]

WHEEL

Wheel-Version: 1.0
Generator: poetry-core 1.5.2
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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LICENSE sha256=kbZSd5WewnN2PSjvAC6DprP7pXx6NUNsnltmU2Mz1yA 34519
models/ProtT5cons_checkpoint.pt sha256=4Bco7aq3YKQIYxwI2DpejSVkdirAs57f6l7EUmCVxNg 3708479
models/VESPA-10LR_Cons_Blsm_Prob.pkl sha256=QWGWssGWBHeUTfJcGfNcKxOBlm_zFsFLPq2gAMZNmWc 4913
models/VESPAl-10LR_Cons_Blsm.pkl sha256=k2wjmr6aTzTQUQrxg77l6deL8XQjz-MfZWEgyr6XU7o 4833
vespa/__init__.py sha256=wKRmEB2zZhCOoenTBMS10XzA9NWpukwUEyf8nEobZIc 243
vespa/predict/config.py sha256=pu8JEbJJdn8bHQspevvH-qKZ58UhM9wp48UTARwNnDo 1982
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vespa/predict/embedding.py sha256=s7GxKbaxsfcyaKThBQceqbAfGJFenlLH-SdXyYeE2ok 3464
vespa/predict/logodds.py sha256=Bk8WSRi5dgVpy3-2FdXiGx_-6V09OlgZX4I55qnUPD4 8305
vespa/predict/utils.py sha256=5db-jHk2h8fKjdSrNMMLU2uygA0DxU1POSL0ugsKOgs 10475
vespa/predict/utils_t5.py sha256=gqwD243ph8DnYIo5TZO_KcBJrDQ0s6kXOJDCgqoZUFE 1228
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vespa/scripts/logodds.py sha256=xYkazmCyJ6sTVQ5Mfe3gwebqKOxvPDPJ0-patEg0h5U 6148
vespa/scripts/meta.py sha256=cuV8OJOxi2tbO2dxOPP8nuNT8ejA2kE2gxHNODexhBo 10654
vespa/scripts/vespa_run.py sha256=VbDATrJwTOKD16ZUuTdLAodgAo5n9JWvv9jJkcS1D2Q 4980
vespa_effect-1.0.2.dist-info/LICENSE sha256=kbZSd5WewnN2PSjvAC6DprP7pXx6NUNsnltmU2Mz1yA 34519
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vespa_effect-1.0.2.dist-info/RECORD — —

entry_points.txt

[console_scripts]
vespa = vespa.scripts.meta:main
vespa_conspred = vespa.scripts.conspred:main
vespa_emb = vespa.scripts.embedding:main
vespa_logodds = vespa.scripts.logodds:main
vespa_run = vespa.scripts.vespa_run:main