---
license: apache-2.0
base_model: allenai/OLMo-2-0425-1B-Instruct
library_name: aether-kit
pipeline_tag: text-generation
tags:
  - core-ai
  - on-device
  - apple
  - macos
  - olmo2
---

# AetherKit OLMo 2 1B Instruct

A Core AI language bundle for [AetherKit](https://github.com/bubstackdev/aether-kit),
ported as a v0.0.6 spike. Source: [allenai/OLMo-2-0425-1B-Instruct](https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct)
at revision `48d788eca847d4d7548f375ad03d3c9312f6139e`, Apache-2.0.

| Folder | Platform | Weights / cache | Attention arithmetic | Context |
| --- | --- | --- | --- | --- |
| `mac/` | macOS 27+ on Apple silicon | float16 | float32 | 4,096 tokens |

`mac/` is a complete registered AetherKit bundle: `language-model.json`,
`model.aimodel/`, `tokenizer/`, and `export-report.json`. The model is specialized
by Core AI on first load. This repository contains the Kit registration format;
use AetherKit's language products to open it.

## Download and use

Download `mac/**` with Hugging Face tooling. Keep the complete directory structure,
then pass the local `mac` directory to `AetherLanguageModel`:

```python
from huggingface_hub import snapshot_download
snapshot_download("aether-models/aether-kit-olmo-2-1b-instruct", allow_patterns=["mac/**", "LICENSE", "NOTICE"], local_dir="olmo2-kit")
```

```swift
import AetherLanguage
import Foundation

let model = AetherLanguageModel(bundle: URL(filePath: "/absolute/olmo2-kit/mac"))
let session = AetherLanguageSession(model: model)
let response = try await session.respond(to: "Explain why the sky is blue.")
print(response.content)
```

For reproducible deployments, pin a repository commit as the download `revision`.
AetherKit's catalog tooling can generate an entry with per-file sizes and SHA-256
values for `ModelPreparation`; this repo does not add automatic downloads to the
runtime.

## Qualification and limits

Exported with Torch 2.11.0, Core AI Torch 0.4.2, and Transformers 4.57.3.
AetherKit source commit: `867b6fe0d56ed16079cfa987cef75297dcc0acde` (the locally integrated v0.0.6 spike;
remote main may not include the export tooling yet).
Evidence in `verification/` refers to exactly the model bytes recorded by the
registration (model SHA-256 `6e3aca1b961acf4f206db3684bd13e77f6f7043de2ab02b805b821d13f8d70ab`).

- 32/32 native GPU argmax rows match an independent upstream float32 reference;
  minimum cosine 0.999999843 and all 64 greedy continuation tokens match.
- 1,024-token decoding completes with zero model reloads and bounded step shapes.
- Full-model CPU self-check, tokenizer chat cases, registered chat, streaming,
  seeded sampling, stop sequences, cancellation recovery, and FoundationModels
  adapter checks pass.
- Qualified on one M5 Max. iOS and other devices are unqualified. The extended
  native session gate exercised 2,048 tokens; the full registered 4,096-token
  context has not been qualified. This is an experimental spike bundle.
- Float32 attention avoids a reproduced fp16 CPU attention near-tie reversal;
  weights and cache storage stay fp16. No paired precision-performance benchmark
  is claimed.

## License and conversion

See `LICENSE` and `NOTICE`. The checkpoint declares Apache-2.0 and provides no
license file; the included license is the canonical Apache-2.0 text. The tokenizer
files are unchanged. Weights were converted to float16 Core AI format. The
upstream model card describes the model's intended uses and limitations.

The export report's local checkpoint path is redacted for publication; source
repository, revision, hashes, versions, and conversion recipe are retained.