Metadata-Version: 2.4
Name: ctt-dual-frequency
Version: 0.2.0
Summary: Physics-based AI compression: 33.27× ratio, 0.8408 correlation. ResNet-18 → 1.34MB.
Home-page: https://github.com/SimoesCTT/The-Chronos-Tensor-Temporal-CTT-Dual-Frequency-Resonance-Compressor
Author: Americo Simoes
Author-email: americo.simoes@example.com
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: torch
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# CTT Dual-Frequency Resonance Compressor

**Physics-based wavefield compression for neural networks.**

- **33.27×** compression ratio
- **0.8408** structural correlation
- **ResNet-18 → 1.34MB**
- **MIT Licensed**
- **PyPI available**

## Installation
```bash
pip install ctt-dual-frequency

from dual_frequency_lzma import CTT2BitResonanceCompresso
### 4. Build and Upload Commands
Once the files are created, run these commands in order:
```bash
# Install build tools (if not already installed)
pip install setuptools wheel twine

# Build the package
python setup.py sdist bdist_wheel

# Upload to PyPI (you'll need an account on pypi.org)
twine upload dist/*
