---
license: cc-by-nc-4.0
library_name: coremltools
pipeline_tag: automatic-speech-recognition
base_model: Audio8/Audio8-ASR-0.1B
language:
  - en
  - zh
  - fr
  - de
  - ja
  - ko
  - yue
tags:
  - coreml
  - apple-silicon
  - automatic-speech-recognition
  - multilingual
  - macos
---

# Audio8-ASR 0.1B — Core ML for Apple Silicon

A ready-to-use hybrid Core ML conversion of [Audio8-ASR-0.1B](https://huggingface.co/Audio8/Audio8-ASR-0.1B) for fast, private, multilingual speech transcription on Apple Silicon.

This model is integrated into [Hugging Mac](https://github.com/devilyouwei/hugging-mac), where you can run it locally and build macOS voice apps, transcription services, plugins, and agents.

> **Non-commercial license:** the model is provided under CC-BY-NC-4.0 and may not be used commercially without separate permission from the upstream rights holder.

## Architecture

This is an explicitly hybrid runtime rather than a fully Core ML autoregressive model:

- The audio encoder and MLP tower run with Core ML on the Apple Neural Engine.
- The cached Qwen2 decoder runs with PyTorch MPS on the GPU.
- A multifunction ML Program provides optimized 5, 10, and 30-second audio buckets.
- Audio-tower weights use INT8 linear quantization with FP16 compute.

The package includes the Core ML audio tower, decoder and projector weights, processor configuration, and reproducible conversion metadata. The tokenizer is downloaded from the pinned upstream model by Hugging Mac.

## Model details

| Property | Value |
|---|---|
| Languages | Chinese, English, French, German, Japanese, Korean, Cantonese |
| Audio | 16 kHz mono, up to 30 seconds |
| Parameters | 0.324B end-to-end; 0.104B language model |
| Core ML target | macOS 15 or later |
| Package size | 429 MB |
| Decoding | Greedy autoregressive decoding with KV cache |

## Core ML functions

| Function | `audios` input | `attn_mask` input | `hidden` output |
|---|---|---|---|
| `tower_5s` | `1 × 128 × 500` FP32 | `1 × 1 × 65 × 65` FP32 | `65 × 1024` FP16 |
| `tower_10s` | `1 × 128 × 1000` FP32 | `1 × 1 × 130 × 130` FP32 | `130 × 1024` FP16 |
| `tower_30s` | `1 × 128 × 3000` FP32 | `1 × 1 × 390 × 390` FP32 | `390 × 1024` FP16 |

Inputs are 128-bin log-Mel features plus an additive attention mask. The default Core ML function is `tower_30s`; Hugging Mac automatically selects the smallest suitable bucket.

## Use with Hugging Mac

Install the ASR dependencies and run the Hugging Mac application:

```bash
git clone https://github.com/devilyouwei/hugging-mac.git
cd hugging-mac
uv sync --all-packages
uv run hugging-mac-web
```

Open the Models page, install **Audio8-ASR 0.1B Core ML**, then use Live Transcription or build against the `SpeechTranscription` capability.

For the full runtime API and implementation, see the [Audio8-ASR SDK package](https://github.com/devilyouwei/hugging-mac/tree/main/packages/hugging_mac_sdk/src/hugging_mac_sdk/models/audio8_asr).

## Provenance

- Upstream model: [Audio8/Audio8-ASR-0.1B](https://huggingface.co/Audio8/Audio8-ASR-0.1B)
- Upstream revision: `8487da63d581fa4fc9b5c60444cb57c3a523d7aa`
- Conversion format: `audio8-asr-coreml-hybrid`
- Conversion metadata: included in `audio8-asr-coreml/conversion.json`
- No upstream remote Python code is included or executed by Hugging Mac.

## Integrity

Directory SHA-256:

```text
6721e90590aee02b6091ec79e3ea451ae1997399e18fcf451f079535a44fce48
```

## License and attribution

The converted model retains the upstream **CC-BY-NC-4.0** license, attribution requirements, and non-commercial restriction. Hugging Mac is an independent open-source project and is not affiliated with or endorsed by Audio8 or AutoArk.