decima for Ollaya

Ollaya package of amyrmahdy/decima-small and amyrmahdy/decima-base and amyrmahdy/decima-agent and amyrmahdy/decima-guard and amyrmahdy/decima-guard-small by A. M. Madani (amyrmahdy). Ollaya runs open decision models locally, the way Ollama runs LLMs: typed questions in, calibrated answers out, behind a TypeSafe-compatible API.

ollaya run decima

What is in this repository

This repository holds only the files Ollaya derives, with no weights. Each graph is an ONNX export of the original model whose weights reference the authors' own weight files by byte offset, so ollaya pull downloads the weights from the upstream repositories, unmodified and pinned to a commit, and verifies their sha256.

Tag Upstream Files
decima:small amyrmahdy/decima-small@2e7f4d0 small/model-fp32.onnx, small/decision.json, small/calibration.json
decima:base amyrmahdy/decima-base@2468005 base/model-fp32.onnx, base/decision.json, base/calibration.json
decima:agent amyrmahdy/decima-agent@652d90a agent/model-fp32.onnx, agent/decision.json, agent/calibration.json
decima:guard amyrmahdy/decima-guard@98d3f73 guard/model-fp32.onnx, guard/decision.json, guard/calibration.json
decima:guard-small amyrmahdy/decima-guard-small@ac11024 guard-small/model-fp32.onnx, guard-small/decision.json, guard-small/calibration.json

Each tag has an fp32 graph, used on CPU and GPU. Each tag also has decision.json (sequence layout, special tokens) and calibration.json (temperatures).

Parity

Ollaya's Rust runtime matches the author's own code at v2.3.0 (decima/model.py, render.py and systemone.py, fp32) on 599 questions from 154 requests for each of small, base, agent 2.3, guard and guard-small, on CPU and CUDA (RTX 4090): identical token rows and truncation, the same 18 rejected requests, the same decision on every question, scores within 3.2e-5 and probabilities within 8.2e-6. Agent's states run to 8,192 tokens: rows of 3,041, 5,986 and 8,076 tokens are kept whole, and one of 8,266 is truncated.

License

Same as the upstream model (Apache-2.0). Ollaya itself is Apache-2.0.

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