Hush AI voice model: NVIDIA Real-time RE-USE 4c0c186, model card and samples

README.md

@@ -1,90 +1,101 @@
----
-license: other
-license_name: nvidia-one-way-noncommercial
-license_link: LICENSE
-base_model: nvidia/Real-time_RE-USE
-pipeline_tag: audio-to-audio
-library_name: hush-ai
-tags:
-  - speech-enhancement
-  - noise-suppression
-  - noise-cancellation
-  - real-time
-  - streaming
-  - mamba
-  - rust
-  - cpu
-  - on-device
----
-
-<p align="center">
-  <img src="icon.png" width="104" alt="Hush AI">
-</p>
-
-<h1 align="center">Hush AI · voice model</h1>
-
-<p align="center">
-  The model files that the <a href="https://github.com/alshell7/hush-ai"><b>Hush AI</b></a> app downloads:
-  free, open-source, on-device noise cancellation for every app.
-</p>
-
-<p align="center">
-  <a href="https://github.com/alshell7/hush-ai/releases/latest"><b>Download the app</b></a> ·
-  <a href="https://alshell7.github.io/hush-ai/"><b>Website</b></a> ·
-  <a href="https://github.com/alshell7/hush-ai"><b>GitHub</b></a>
-</p>
-
-![Hush AI app and tray widget](https://raw.githubusercontent.com/alshell7/hush-ai/main/assets/screenshots/hero.png)
-
-## What is here
-
-| File | Contents |
-| --- | --- |
-| `models/realtime-reuse-4c0c186.safetensors` | NVIDIA [Real-time RE-USE](https://huggingface.co/nvidia/Real-time_RE-USE) weights, revision `4c0c186`, **unchanged** (FP32, 13.5 M parameters, 54 MB) |
-| `models/SHA256SUMS` | `6eac4e8cc721f99a22cde7eac3c9f8e2826ced5dc8a4234fd1977de1ec0d3ade` |
-| `samples/noisy.mp3`, `samples/hush.mp3` | NVIDIA's sample recording, before and after Hush AI |
-| `LICENSE` | The NVIDIA One-Way Noncommercial License that covers the weights and samples |
-
-The app checks the SHA-256 before it uses the file. If this mirror is unreachable, it
-downloads the same file from NVIDIA's repository at the same revision.
-
-## How Hush AI runs the model
-
-[Hush AI](https://github.com/alshell7/hush-ai) runs Real-time RE-USE in native Rust on
-the CPU, one 20 ms frame at a time, with no Python, GPU or network. It removes background
-noise from your microphone and gives every app a clean **Hush AI Microphone**.
-
-| Quality | Model setting | Apple M1, 2 threads (p99 per 20 ms frame) |
-| --- | --- | ---: |
-| Light (app default) | 16 kHz, 3 layers | 11.7 ms |
-| Balanced | 24 kHz, 4 layers | 21.3 ms |
-| Studio | 48 kHz, 3 layers | 36.8 ms |
-
-- **Delay:** about 60–80 ms plus device buffers.
-- **Accuracy:** NVIDIA's seven GPU regression cases pass in CI on Windows, macOS and Linux.
-  The CPU output matches NVIDIA's GPU reference at 113–118 dB waveform SNR on short speech.
-- **Comparison:** measured against DeepFilterNet 3 and RNNoise on VoiceBank-DEMAND in
-  [COMPARISON.md](https://github.com/alshell7/hush-ai/blob/main/docs/COMPARISON.md).
-
-Use the weights from Rust with the [`hush-core`](https://github.com/alshell7/hush-ai/tree/main/crates/hush-core) crate:
-
-```rust
-let mut denoiser = hush_core::Denoiser::with_config(
-    "models/realtime-reuse-4c0c186.safetensors",
-    hush_core::Config { layers: 3, sample_rate: 16_000, look_ahead: 0 },
-)?;
-let mut clean = Vec::new();
-denoiser.process_into(&noisy_chunk, &mut clean)?;
-```
-
-## License
-
-The weights and the samples are NVIDIA's work, redistributed unchanged under the
-**NVIDIA One-Way Noncommercial License** ([LICENSE](LICENSE)): use them for
-**non-commercial research and educational purposes only**. NVIDIA Corporation and its
-affiliates may use them commercially. See the original
-[NVIDIA model card](https://huggingface.co/nvidia/Real-time_RE-USE) for the model,
-its training and its papers.
-
-The Hush AI app and engine are Apache-2.0. Hush AI is an independent project and is not
-affiliated with or endorsed by NVIDIA.
+---
+license: other
+license_name: nvidia-one-way-noncommercial-and-mit-apache
+license_link: LICENSE
+base_model: nvidia/Real-time_RE-USE
+pipeline_tag: audio-to-audio
+library_name: hush-ai
+tags:
+  - speech-enhancement
+  - noise-suppression
+  - noise-cancellation
+  - real-time
+  - streaming
+  - mamba
+  - deepfilternet
+  - rust
+  - cpu
+  - on-device
+---
+
+<p align="center">
+  <img src="icon.png" width="104" alt="Hush AI">
+</p>
+
+<h1 align="center">Hush AI · voice models</h1>
+
+<p align="center">
+  The model files that the <a href="https://github.com/alshell7/hush-ai"><b>Hush AI</b></a> app downloads:
+  free, open-source, on-device noise cancellation for every app.
+</p>
+
+<p align="center">
+  <a href="https://github.com/alshell7/hush-ai/releases/latest"><b>Download the app</b></a> ·
+  <a href="https://alshell7.github.io/hush-ai/"><b>Website</b></a> ·
+  <a href="https://github.com/alshell7/hush-ai"><b>GitHub</b></a>
+</p>
+
+![Hush AI app and tray widget](https://raw.githubusercontent.com/alshell7/hush-ai/main/assets/screenshots/hero.png)
+
+## What is here
+
+| File | Contents | License |
+| --- | --- | --- |
+| `models/DeepFilterNet3_onnx-v0.5.6.tar.gz` | [DeepFilterNet 3](https://github.com/Rikorose/DeepFilterNet) by Hendrik Schröter, from release `v0.5.6`, **unchanged** (ONNX encoder and two decoders, 8 MB) | MIT or Apache-2.0 |
+| `models/realtime-reuse-4c0c186.safetensors` | NVIDIA [Real-time RE-USE](https://huggingface.co/nvidia/Real-time_RE-USE) weights, revision `4c0c186`, **unchanged** (FP32, 13.5 M parameters, 54 MB) | NVIDIA One-Way Noncommercial |
+| `models/SHA256SUMS` | SHA-256 of both model files | |
+| `samples/noisy.mp3`, `samples/hush.mp3` | NVIDIA's sample recording, before and after Hush AI | NVIDIA One-Way Noncommercial |
+
+The app checks the SHA-256 before it uses a file. If this mirror is unreachable, it
+downloads the same file from its original source at the same version.
+
+## How Hush AI runs the models
+
+[Hush AI](https://github.com/alshell7/hush-ai) has two engines, and you can switch between them
+in the app. Both run on the CPU, with no Python, GPU or network:
+
+- **DeepFilterNet 3**: the official Rust inference (libDF with tract), 48 kHz, 10 ms frames.
+  Light on the CPU, and its license allows commercial use.
+- **NVIDIA Real-time RE-USE**: a native Rust port of NVIDIA's Mamba model, 20 ms frames.
+
+RE-USE quality settings in the app:
+
+| Quality | Model setting | Apple M1, 2 threads (p99 per 20 ms frame) |
+| --- | --- | ---: |
+| Light (app default) | 16 kHz, 3 layers | 11.7 ms |
+| Balanced | 24 kHz, 4 layers | 21.3 ms |
+| Studio | 48 kHz, 3 layers | 36.8 ms |
+
+- **Delay:** about 60–80 ms plus device buffers.
+- **Accuracy:** NVIDIA's seven GPU regression cases pass in CI on Windows, macOS and Linux.
+  The CPU output matches NVIDIA's GPU reference at 113–118 dB waveform SNR on short speech.
+- **Comparison:** measured against DeepFilterNet 3 and RNNoise on VoiceBank-DEMAND in
+  [COMPARISON.md](https://github.com/alshell7/hush-ai/blob/main/docs/COMPARISON.md).
+
+Use the RE-USE weights from Rust with the [`hush-core`](https://github.com/alshell7/hush-ai/tree/main/crates/hush-core) crate:
+
+```rust
+let mut denoiser = hush_core::Denoiser::with_config(
+    "models/realtime-reuse-4c0c186.safetensors",
+    hush_core::Config { layers: 3, sample_rate: 16_000, look_ahead: 0 },
+)?;
+let mut clean = Vec::new();
+denoiser.process_into(&noisy_chunk, &mut clean)?;
+```
+
+## Licenses
+
+- **DeepFilterNet 3** (`models/DeepFilterNet3_onnx-v0.5.6.tar.gz`): © Hendrik Schröter, MIT
+  ([LICENSE-DeepFilterNet-MIT](models/LICENSE-DeepFilterNet-MIT)) or Apache-2.0
+  ([LICENSE-DeepFilterNet-APACHE](models/LICENSE-DeepFilterNet-APACHE)), at your option.
+  Commercial use is allowed. Paper: Schröter et al., *DeepFilterNet: Perceptually Motivated
+  Real-Time Speech Enhancement*, Interspeech 2023.
+- **Real-time RE-USE** (`models/realtime-reuse-4c0c186.safetensors`) and the samples:
+  NVIDIA's work, redistributed unchanged under the **NVIDIA One-Way Noncommercial License**
+  ([LICENSE](LICENSE)): **non-commercial research and educational use only**. NVIDIA
+  Corporation and its affiliates may use them commercially. See the original
+  [NVIDIA model card](https://huggingface.co/nvidia/Real-time_RE-USE) for the model, its
+  training and its papers.
+
+The Hush AI app and engine are Apache-2.0. Hush AI is an independent project and is not
+affiliated with or endorsed by NVIDIA or the DeepFilterNet authors.

models/DeepFilterNet3_onnx-v0.5.6.tar.gz

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+version https://git-lfs.github.com/spec/v1
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+size 7983136

models/LICENSE-DeepFilterNet-APACHE

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models/LICENSE-DeepFilterNet-MIT

@@ -0,0 +1,19 @@
+The MIT License (MIT)
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models/SHA256SUMS

@@ -1 +1,2 @@
 6eac4e8cc721f99a22cde7eac3c9f8e2826ced5dc8a4234fd1977de1ec0d3ade *realtime-reuse-4c0c186.safetensors
+c94d91f70911001c946e0fabb4aa9adc37045f45a03b56008cb0c8244cb63616 *DeepFilterNet3_onnx-v0.5.6.tar.gz