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| tags: | |
| - vbl | |
| - recurrent | |
| - x86-64 | |
| - avx2 | |
| - rust | |
| - cpu | |
| - full-ram | |
| - research | |
| library_name: custom | |
| # VBL-32M-Utility Native | |
| **31,974,240-parameter VBL utility/research release with a native Rust x86_64 runtime.** | |
| ## Native execution | |
| The primary runtime is **not Python/PyTorch**. | |
| - Rust x86_64 | |
| - AVX2 + FMA optimized CPU dot products | |
| - FP32 weights | |
| - all model weights loaded into process RAM at startup | |
| - **no mmap** | |
| - **no SSD/model streaming** | |
| - no quantization | |
| - no GPU required for runtime | |
| FP32 neural parameter payload: **121.97 MiB**. | |
| ## Neural architecture | |
| Active checkpoint architecture: | |
| `input -> embedding -> prelude -> [V16_NORM_MEAN + state-conditioned elastic bank + shared recurrent core] x R2 -> coda -> tied output` | |
| - base VBL-RC M0: 20,013,920 parameters | |
| - connected elastic capacity: 11,960,320 parameters | |
| - total: 31,974,240 | |
| - 73 experts | |
| - expert width: 320 -> 256 -> 320 | |
| - top-k: 3 | |
| - router: token-causal, shares expert `down.weight[0]`, zero additional router parameters | |
| - selected experimental alpha: 0.75 | |
| ## Verification status | |
| This repository is intentionally named **Utility**, not Verified-32M. | |
| The 32M candidate's official frozen C1 result was: | |
| **583 / 853** | |
| Therefore it is **NOT KR100 promoted**. The canonical M0 lineage remains preserved in the 32M base weights. | |
| ## Utility mode | |
| The native executable loads the complete 32M model into RAM and first routes deterministic tasks | |
| through executable verifiers. Unsupported utility requests abstain instead of fabricating a result. | |
| Examples: | |
| ```bash | |
| ./vbl32m --model-dir . "What is 34 + -13?" | |
| ./vbl32m --model-dir . "Is 772 even or odd?" | |
| ./vbl32m --model-dir . "Complete the sequence: 32, 33, 34, 35," | |
| ``` | |
| Raw experimental neural generation: | |
| ```bash | |
| ./vbl32m --model-dir . --raw "User: What is 2 + 2? Assistant:" | |
| ``` | |
| Trace recurrent state convergence: | |
| ```bash | |
| ./vbl32m --model-dir . --raw --trace "User: Hello Assistant:" | |
| ``` | |
| ## Windows x86_64 | |
| The repository includes `native/build-windows-x86_64.ps1`. | |
| On an x86_64 Windows machine with Rust installed: | |
| ```powershell | |
| cd native | |
| .uild-windows-x86_64.ps1 | |
| ``` | |
| This produces `native arget eleasebl32m.exe`. | |
| ## VBL architecture policy | |
| See `ARCHITECTURE.json`. | |
| Features that were approved as experimental directions but were not trained/certified in this exact | |
| checkpoint are explicitly marked inactive instead of being falsely presented as learned behavior. | |
| Full-RAM residency intentionally disables predictive SSD streaming/prefetch. | |
| ## Files | |
| - `model.safetensors` β complete 32M FP32 state | |
| - `tokenizer.json` β VBL-BPE-24K | |
| - `native_config.json` β native runtime configuration and parity proof | |
| - `native/` β Rust source | |
| - `bin/linux-x86_64-v3/vbl32m` β compiled Linux x86_64 AVX2/FMA binary | |
| - `ARCHITECTURE.json` β active/inactive VBL architecture contract | |
| - `MANIFEST.json` / `SHA256SUMS` β provenance | |