Factual package intelligence from PyPI
Estimate, benchmark, and generate fine-tuning recipes for LLMs on consumer GPUs.
pip install canifinetune
PyPI declares 23 unique dependency rules for this release. Environment markers are shown when supplied by the project.
>=0.25>=3.1>=4.2>=2.6>=6.0>=13.7>=0.12The compact report shows 12 of 23 declarations. The interactive dependency graph loads the complete metadata.
canifinetune publishes 1 wheel and 1 source archive for version 0.3.0. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.11, 3.12, 3.13, 3.14.
PyPI lists 4 releases with files. The first dated release is ; 4 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .