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license: apache-2.0
base_model:
- EldanRing/Winnow-12B
- EldanRing/Winnow-E4B
tags:
- ollaya
- gguf
- llama.cpp
- decision-model
- system-one
pipeline_tag: text-classification
---
# winnow for Ollaya
[Ollaya](https://github.com/ollaya-dev/ollaya) package of **[EldanRing/Winnow-12B](https://huggingface.co/EldanRing/Winnow-12B)** and **[EldanRing/Winnow-E4B](https://huggingface.co/EldanRing/Winnow-E4B)** by EldanRing.
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 winnow
```
## What is in this repository
This repository holds only the files Ollaya derives, with no weights. The model is the authors' own GGUF
file: `ollaya pull` downloads it from their repository, unmodified and pinned to a commit, verifies its
sha256, and Ollaya runs it on llama.cpp.
| Tag | The authors' GGUF | Files |
|---|---|---|
| `winnow:12b` | [EldanRing/Winnow-12B@b6ac22b](https://huggingface.co/EldanRing/Winnow-12B/tree/b6ac22b0d51b69b18200acacb3fbdd98073fffe8) `gguf/Winnow-12B-Q8_0.gguf` | `12b/decision.json`, `12b/calibration.json` |
| `winnow:e4b` | [EldanRing/Winnow-E4B@734302f](https://huggingface.co/EldanRing/Winnow-E4B/tree/734302fe5fbfeb3f21a7ece62653c9539be4aaf3) `gguf/Winnow-E4B-Q8_0.gguf` | `e4b/decision.json`, `e4b/calibration.json` |
| `winnow:12b-vision` | [EldanRing/Winnow-12B@b6ac22b](https://huggingface.co/EldanRing/Winnow-12B/tree/b6ac22b0d51b69b18200acacb3fbdd98073fffe8) `gguf/Winnow-12B-Q8_0.gguf` + `gguf/mmproj-Winnow-12B.gguf` | `12b-vision/decision.json`, `12b-vision/calibration.json` |
| `winnow:e4b-vision` | [EldanRing/Winnow-E4B@734302f](https://huggingface.co/EldanRing/Winnow-E4B/tree/734302fe5fbfeb3f21a7ece62653c9539be4aaf3) `gguf/Winnow-E4B-Q8_0.gguf` + `gguf/mmproj-Winnow-E4B.gguf` | `e4b-vision/decision.json`, `e4b-vision/calibration.json` |
Each tag has `decision.json` (the prompt, the option labels Ollaya reads and llama.cpp's settings) and
`calibration.json` (temperatures). A vision tag also pulls the authors' vision projector from the same revision, which reads the images.
## Parity
Ollaya's runner matches stock llama-server of the pinned build (b11146) on the same GGUF and the same device: 505 text questions per model, every decision the same, option logits within 1.3e-5 and probabilities within 3.0e-6, on CUDA (RTX 4090, Linux and Windows) and, for e4b, the x86-64 CPU. With the vision projector, 65 image questions per model, every decision the same, option logits within 1.2e-5 (RTX 4070, RTX 5090 and the x86-64 CPU).
## License
Same as the upstream model (Apache-2.0). Ollaya itself is Apache-2.0.
|