license: apache-2.0
base_model:
- amyrmahdy/decima-small
- amyrmahdy/decima-base
- amyrmahdy/decima-agent
library_name: onnx
tags:
- ollaya
- onnx
- decision-model
- system-one
pipeline_tag: text-classification
decima for Ollaya
Ollaya package of amyrmahdy/decima-small and amyrmahdy/decima-base and amyrmahdy/decima-agent 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@86a07aa | agent/model-fp32.onnx, agent/decision.json, agent/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 (decima/model.py and systemone.py, fp32) on 581 questions from 122 requests for each of small, base and agent, on CPU and CUDA (RTX 4090 and RTX 5090): identical token rows and truncation, the same 18 rejected requests, the same decision on every question, scores within 2.0e-5 and probabilities within 5.5e-6.
License
Same as the upstream model (Apache-2.0). Ollaya itself is Apache-2.0.