LeonaQuantum/leonaq-1-mini
AI model by LeonaQuantum
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1.76 GB model · Four coherent circuit paths · 2.06× faster decoding Leona-Q 1.0 mini brings quantum-inspired tensor compression and learned quantum-circuit interference into a compact language model based on MiniCPM5-2B. MPO correction preserves structure lost during low-bit quantization. A four-path square circuit adds a learned interference-driven residual during inference. 量子inspiredなMPO圧縮と、4経路の量子干渉回路を組み合わせた小型LLM。圧縮したまま回路を推論に使い、独自の直接MPO計算で生成を高速化しています。 The quantum circuits run as classical statevector simulations; no quantum computer is required. This release uses a custom Linux/CUDA runtime. The circuit can be switched on or off independently of MPO compression. The following accuracy results evaluate the same Leona-Q 1.0 mini weights and circuit checkpoint using the earlier BF16 reconstruction runtime. They are reference model results; the new direct-MPO runtime has separate numerical validation below and has not yet repeated these task benchmarks. One generated answer per question, thinking enabled, temperature 1, top-p 0.95, no top-k filtering; natural EOS or the 131,072-token context boundary. This is a single-sample…
Read the full model card ↗ · Preview checked 2026-10-30T02:32:28.331Z
Inside the original model card — Document outline
- Leona-Q 1.0 mini
- MPO compression meets quantum-circuit interference.
- The architecture
- Benchmark results
- AIME 2026
- Seven full-split language benchmarks
- Optimized decoding speed
- Try it
- Provenance
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Model overview
LeonaQuantum/leonaq-1-mini is a task-unspecified model repository published by LeonaQuantum on Hugging Face. A library was not reported.
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- apache-2.0
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- Created
- 2026-10-13T06:26:17.000Z
- Last modified
- 2026-10-13T06:26:17.000Z
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