README.md

---
license: apache-2.0
base_model:
- Contrastive-LM/CLM-v0.1-8B
- Qwen/Qwen3-8B
library_name: onnx
tags:
- ollaya
- onnx
- decision-model
- system-one
pipeline_tag: text-classification
---

# clm for Ollaya

[Ollaya](https://github.com/ollaya-dev/ollaya) package of **[Contrastive-LM/CLM-v0.1-8B](https://huggingface.co/Contrastive-LM/CLM-v0.1-8B)** and **[Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)** by Contrastive-LM (projection heads) and the Qwen team (Qwen3-8B encoder).
Ollaya runs open decision models locally, the way Ollama runs LLMs: typed questions in,
calibrated answers out, behind a TypeSafe-compatible API.

```sh
ollaya run clm
```

## 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 |
|---|---|---|
| `clm:8b` | [Contrastive-LM/CLM-v0.1-8B@e939398](https://huggingface.co/Contrastive-LM/CLM-v0.1-8B/tree/e939398d4556fcd9400c76fa8c5a513202f42b0a), [Qwen/Qwen3-8B@b968826](https://huggingface.co/Qwen/Qwen3-8B/tree/b968826d9c46dd6066d109eabc6255188de91218) | `8b/model-fp32.onnx`, `8b/decision.json`, `8b/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 reference (upstream clm.schema and heads, the Qwen3-8B encoder in fp32 on its BF16 weights) on 480 questions from 117 requests, on CPU and CUDA: the same state and option texts and token ids, the same rejections, the same decision on every question, option logits within 1.3e-4 and probabilities within 2.9e-5.

## License

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