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| title: README | |
| emoji: 🚀 | |
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| # Refract AI Labs | |
| **Refract AI Labs** is an experimental AI research group focused on efficient language-model architectures, compact reasoning systems, and unconventional alternatives to standard dense Transformers. | |
| We build small models, weird architectures, and research prototypes with one main goal: | |
| > **Maximum capability, minimum parameters.** | |
| ## News | |
| **28 September 2026** Refract AI is now a seperate group from smilyai! | |
| **29 September 2026** We have collected over 50B tokens in preperation for the Orion-T2.1 Pretraining run. | |
| ## Current projects | |
| ### Orion / Project Prism | |
| **Orion** is our experimental language-model family exploring: | |
| - explicit temporary working state | |
| - recurrent computation | |
| - parameter reuse | |
| - sparse conditional computation | |
| - compact knowledge and procedure mechanisms | |
| - hybrid base + instruction training | |
| The current public model is: | |
| **Orion Flagship Mini** | |
| A ~219M parameter custom-architecture causal language model and instruction-tuned assistant. | |
| Model: | |
| https://huggingface.co/Refract-Labs/Orion-Flagship-Mini | |
| Base model: | |
| https://huggingface.co/Refract-Labs/Orion-Flagship-Mini-Base | |
| ## Research direction | |
| We are especially interested in: | |
| - efficient LLM architectures | |
| - recurrent and iterative reasoning | |
| - alternatives to scaling parameter count | |
| - parameter-efficient computation | |
| - long-context behavior | |
| - model memory and working state | |
| - post-training and hybrid training methods | |
| - small-model capability research | |
| ## Philosophy | |
| We like experiments that are: | |
| - measurable | |
| - reproducible | |
| - honest about limitations | |
| - interesting even when they fail | |
| Architecture claims should be tested with controlled comparisons rather than assumed from design alone. | |
| ## Open research | |
| Some Refract AI Labs models and code are released publicly for research, experimentation, and community feedback. | |
| Expect prototypes, unfinished ideas, occasional cursed training runs, and hopefully a few genuinely useful discoveries. 🧪 | |
| --- | |
| Part of the wider **SmilyAI** research ecosystem. (still kinda) | |