THIRD_PARTY_LICENSES.md

# Third-Party Licenses

This repository redistributes the following third-party machine-learning
models in pre-converted **Core ML** form. Each entry below names the
component and the archive it ships in, identifies the upstream source,
reproduces the upstream copyright statement, and points to the verbatim
license text required by that component's license.

Most of the models are licensed under the Apache License, Version 2.0; two
(Silero VAD and BEATs) are licensed under the MIT License. The verbatim
license texts are reproduced in the appendices at the end of this file.

| Archive | Component | License |
| --- | --- | --- |
| `qwen3_5_mlx_4b_vision_vid_512x320_w8.tar` | Qwen3.5 vision tower | Apache-2.0 ([Appendix A](#appendix-a-apache-license-version-20)) |
| `qwen3_5_mlx_4b_vision_vid_768x480_w8.tar` | Qwen3.5 vision tower | Apache-2.0 ([Appendix A](#appendix-a-apache-license-version-20)) |
| `gemma4_mlx_e4b_vision_768x480_w8.tar` | Gemma 4 vision tower | Apache-2.0 ([Appendix A](#appendix-a-apache-license-version-20)) |
| `yolox_l_1024x640_w8.tar` | YOLOX | Apache-2.0 ([Appendix A](#appendix-a-apache-license-version-20)) |
| `silero-vad-unified-v6.tar` | Silero VAD (FluidInference Core ML conversion) | MIT ([Appendix B](#appendix-b-mit-license)) |
| `beats_as2m_10s.tar` | BEATs (microsoft/unilm) | MIT ([Appendix B](#appendix-b-mit-license)) |

---

## Qwen3.5 (vision tower)

The archives `qwen3_5_mlx_4b_vision_vid_512x320_w8.tar` and
`qwen3_5_mlx_4b_vision_vid_768x480_w8.tar` contain Core ML conversions of
the **Qwen3.5-4B** vision tower (the multimodal vision encoder) at two input
resolutions, derived from the Qwen3.5 model series published by the Qwen
team at Alibaba Cloud (<https://huggingface.co/Qwen>). The weights are
8-bit-quantized and the graph is exported to Core ML; the model is otherwise
a derivative of the upstream Qwen3.5 weights.

Qwen3.5 open-weight models are distributed under the Apache License,
Version 2.0.

### Copyright notice

Reproduced from the upstream `LICENSE`:

> Copyright 2024 Alibaba Cloud

### License

Apache License, Version 2.0. The verbatim text is reproduced in
[Appendix A](#appendix-a-apache-license-version-20), and is available
upstream at
<https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE> and
<https://www.apache.org/licenses/LICENSE-2.0>.

---

## Gemma 4 (vision tower)

The archive `gemma4_mlx_e4b_vision_768x480_w8.tar` contains a Core ML
conversion of the **Gemma 4 (e4b)** vision tower (the multimodal vision
encoder that projects image features into the language model's text
embedding space), derived from the Gemma 4 model series published by Google
DeepMind (<https://huggingface.co/google/gemma-4-E4B>). The weights are
int8 weight-only quantized and the graph is exported to Core ML; the model
is otherwise a derivative of the upstream Gemma 4 weights.

Gemma 4 open-weight models are distributed under the Apache License,
Version 2.0. (This differs from earlier Gemma releases, which used the
custom Gemma Terms of Use.)

### Copyright notice

> Copyright Google LLC

The upstream model card declares the license as Apache-2.0; Google does not
publish a per-file copyright line for the Gemma 4 weights.

### License

Apache License, Version 2.0. The verbatim text is reproduced in
[Appendix A](#appendix-a-apache-license-version-20), and is available
upstream at
<https://ai.google.dev/gemma/docs/gemma_4_license> and
<https://www.apache.org/licenses/LICENSE-2.0>.

---

## YOLOX

The archive `yolox_l_1024x640_w8.tar` contains a Core ML conversion of
**YOLOX-L**, the anchor-free object detector from Megvii Inc.
(<https://github.com/Megvii-BaseDetection/YOLOX>). The weights are
8-bit-quantized and exported to Core ML at a 1024×640 input; the model is
otherwise a derivative of the upstream YOLOX-L weights.

YOLOX is distributed under the Apache License, Version 2.0.

### Copyright notice

Reproduced verbatim from
<https://github.com/Megvii-BaseDetection/YOLOX/blob/main/LICENSE>:

> Copyright (c) 2021-2022 Megvii Inc. All rights reserved.

### License

Apache License, Version 2.0. The verbatim text is reproduced in
[Appendix A](#appendix-a-apache-license-version-20), and is available
upstream at
<https://github.com/Megvii-BaseDetection/YOLOX/blob/main/LICENSE>.

---

## Silero VAD

The archive `silero-vad-unified-v6.tar` contains the **Silero VAD v6.0.0**
unified Core ML model (STFT + encoder + decoder in one graph). The
underlying voice-activity-detection model is Silero VAD by the Silero Team
(<https://github.com/snakers4/silero-vad>); the Core ML conversion
redistributed here is from FluidInference
(<https://huggingface.co/FluidInference/silero-vad-coreml>). Both the
original model and the FluidInference conversion are distributed under the
MIT License.

### Copyright notice

Reproduced verbatim from
<https://github.com/snakers4/silero-vad/blob/master/LICENSE>:

> Copyright (c) 2020-present Silero Team

The FluidInference Core ML conversion credits both the Silero Team
(original model) and the FluidAudio Team (conversion) and is itself
released under the MIT License.

### License

MIT License. The verbatim text is reproduced in
[Appendix B](#appendix-b-mit-license), and is available upstream at
<https://github.com/snakers4/silero-vad/blob/master/LICENSE>.

---

## BEATs

The archive `beats_as2m_10s.tar` contains a Core ML conversion of **BEATs**
(iter3+, fine-tuned on AudioSet-2M, `cpt1` checkpoint), the audio
representation model from Microsoft's `unilm` project
(<https://github.com/microsoft/unilm/tree/master/beats>). The graph is
exported to Core ML over a fixed 10-second window; the model is otherwise a
derivative of the upstream BEATs weights.

BEATs is distributed under the MIT License (the `microsoft/unilm` repository
license).

### Copyright notice

Reproduced verbatim from
<https://github.com/microsoft/unilm/blob/master/LICENSE>:

> Copyright (c) Microsoft Corporation

### License

MIT License. The verbatim text is reproduced in
[Appendix B](#appendix-b-mit-license), and is available upstream at
<https://github.com/microsoft/unilm/blob/master/LICENSE>.

---

# Appendix A: Apache License, Version 2.0

The Qwen3.5 and Gemma 4 vision towers and the YOLOX model above are all
distributed under the following license, reproduced verbatim.

```
                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

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   APPENDIX: How to apply the Apache License to your work.

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   Copyright [yyyy] [name of copyright owner]

   Licensed under the Apache License, Version 2.0 (the "License");
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```

---

# Appendix B: MIT License

The Silero VAD and BEATs models above are distributed under the following
license, reproduced verbatim. The text is identical for both; only the
copyright line differs (given in each component's section above — Silero
Team for Silero VAD, Microsoft Corporation for BEATs). The copy below shows
the Silero VAD copyright line.

```
MIT License

Copyright (c) 2020-present Silero Team

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
```