# CoNDeNse

> **Compress the knowledge. Keep the capability.**

CoNDeNse is a research org built around one idea: small models don't have to be dumb. We take compact, efficient model architectures and train them on the reasoning traces and outputs of models many times their size — distilling capability downward without bloating parameter counts upward.

The name says it all: **Con**dense. Take what's big. Make it small. Lose as little as possible.

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## Philosophy

- **No fluff.** We don't chase benchmarks with tricks. We train honestly and report honestly.
- **Smol is serious.** A 0.6B model that reasons is more useful than a 70B model you can't run.
- **Quality data > more data.** Every dataset we use is curated, filtered, and purposefully scoped.
- **Reproducibility first.** If you can't replicate it, it didn't happen.

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## Support CoNDeNse

CoNDeNse is a solo research effort. There's no lab, no grant, no GPU cluster behind this — just genuine curiosity and a conviction that small models deserve better training.

The best way to support the work right now is simple: **download and use the models.** Every download signals that this direction matters. If a model works well for you, star the repo, share it, or drop a comment on the model card.

If you want to go further — contributions, dataset suggestions, or collaboration ideas — open an issue or reach out directly.

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## License

All released models inherit the license of their respective base models. Dataset usage follows the terms of the original dataset authors. Training code is MIT.

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*CoNDeNse — because the best model is the one that actually runs.*