TMLM-Haiku-2.3

It speaks. It actually speaks. Mostly.

We have come so far. From the dark ages of couldcouldoldbloodblood to actual, coherent, structured sentences. This is TMLM-Haiku-2.3. It is 1 million parameters. It is small. It is trying its best. And unlike its ancestors, it usually succeeds.

Quick Stats

  • Parameters: 1,000,000 (Yes, really. 1M.)
  • Training Tokens: 10 Billion
  • Context Window: 2048 tokens
  • Vibe: Chaotic good, but mostly good.

What Is This?

Haiku-2.3 is the latest evolution of the TMLM-Haiku series. It builds on Haiku-2 by adding SPIN (Self-Play Fine-Tuning) to the training loop. This model represents a 3x improvement in combined performance score over the original Haiku. Coherence has jumped from 1.99 to 6.03. Relevance is no longer zero. It is a miracle.

The Journey

Model Era Typical Output Combined Score
Haiku-1 The Dark Ages couldcouldoldbloodbloodbodybody 1.62
Haiku-1.3 The Pipe Character Incident |fdish|||||!@| 1.21
Haiku-2 The Awakening It is about **competent development**... 3.87
Haiku-2.3 (SPIN) Current Era The artificial intelligence is a problem... 4.84 ★

Expected Output:

"The simple terms arrived in simulant explorers and honey are specific or forecasters. They allow the structure of their similar..."

Disclaimer

This is a 1 million parameter model.

  • It is not GPT-5.
  • It is not GPT-2.
  • It is a tiny neural network running on a prayer and a GPU.
  • It might still output chuamliamce occasionally. If it does, just try again. It is shy.
  • For best results, use temperature around 0.7. If you crank it to 2.0, you are on your own.

Benchmarks

We benchmarked Haiku-2.3 against all previous versions using a standard 7-question suite.

Metric Haiku-1 Haiku-1.3 Haiku-2 Haiku-2.3 (SPIN)
Fluency 0.50 1.69 8.35 8.78
Coherence 1.99 1.56 5.72 6.03
Relevance 1.22 0.00 0.00 2.25
Format 3.29 3.29 3.29 3.29
Combined 1.62 1.21 3.87 4.84

Related Models

Check out the rest of the family:

Acknowledgments

Built with curiosity over compute. Trained on FineWeb-Edu. SPIN optimized. And a lot of hope.


Built by CompactAI. If you like tiny models that try their best, give us a follow. ```

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