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A transformer-based model for time series forecasting inspired by modern attention mechanisms
pip install temporal-forecasting
PyPI declares 30 unique dependency rules for this release. Environment markers are shown when supplied by the project.
>=2.0.0>=1.20.0>=4.60.0>=3.3.0The compact report shows 25 of 30 declarations. The interactive dependency graph loads the complete metadata.
temporal-forecasting publishes 1 wheel and 1 source archive for version 0.3.4. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.11, 3.12, 3.8, 3.9.
PyPI lists 7 releases with files. The first dated release is ; 7 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .