---
license: mit
base_model:
- MoritzLaurer/deberta-v3-large-zeroshot-v2.0
- MoritzLaurer/ModernBERT-large-zeroshot-v2.0
library_name: onnx
tags:
- ollaya
- onnx
- decision-model
- system-one
pipeline_tag: text-classification
---

# nli for Ollaya

[Ollaya](https://github.com/ollaya-dev/ollaya) package of **[MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0)** and **[MoritzLaurer/ModernBERT-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/ModernBERT-large-zeroshot-v2.0)** by Moritz Laurer.
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 nli
```

## 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 author's own `model.safetensors` by byte offset**,
so `ollaya pull` downloads the weights from the upstream repository, unmodified and pinned to a
commit, and verifies their sha256.

| Tag | Upstream | Files |
|---|---|---|
| `nli:deberta-v3-large` | [MoritzLaurer/deberta-v3-large-zeroshot-v2.0@cf44676](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0/tree/cf44676c28ba7312e5c5f8f8d2c22b3e0c9cdae2) | `deberta-v3-large/model-fp32.onnx`, `deberta-v3-large/decision.json`, `deberta-v3-large/calibration.json` |
| `nli:modernbert-large` | [MoritzLaurer/ModernBERT-large-zeroshot-v2.0@a51e07b](https://huggingface.co/MoritzLaurer/ModernBERT-large-zeroshot-v2.0/tree/a51e07b524299e309dd2b88d48b0cfa2bd9ec598) | `modernbert-large/model-fp32.onnx`, `modernbert-large/decision.json`, `modernbert-large/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 Python reference exactly on 483 questions (1,513 hypothesis rows) per model. The token ids are identical, and so is the decision on every question. Probabilities are within 2.5e-5, on CPU and CUDA.

## License

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