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DeepFilterNet3-ONNX
tonythethompson/DeepFilterNet3-ONNX
DeepFilterNet3-ONNX is a audio-to-audio model from tonythethompson. Use it for the audio-to-audio task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This repository contains ONNX exports for DeepFilterNet3, a speech enhancement and noise suppression model.
Access
Public
Updated Jun 15, 2026
Repo size
8.6 MB
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.onnx8.6 MB · 100%
At a glance
- Task
- Audio-to-Audio
- License
- apache-2.0
- Access
- Public
- Created
- May 21, 2026
- Updated
- Jun 15, 2026
- SHA
- 191b1021
Model card
From the Hugging Face model README
deepfilternet3-onnx
Overview
This repository contains ONNX exports for DeepFilterNet3, a speech enhancement and noise suppression model.
Source
| Field | Value |
|---|---|
| Upstream model | Rikorose/DeepFilterNet (DeepFilterNet3 weights) |
| Upstream source revision | dcbbe520263d1061693c4c4a56a6d6a917f30b25 |
| Packaging source revision | dcbbe520263d1061693c4c4a56a6d6a917f30b25 |
| Export tool/script | torch.onnx export from DeepFilterNet3 checkpoint |
| Quantization recipe | FP32 ONNX (enc.onnx, erb_dec.onnx, df_dec.onnx) |
| Notes | Upstream weights are from the DeepFilterNet GitHub project; ONNX graphs are pinned at the packaging revision above. |
Precision and Packaging
Export tooling, precision, and quantization are recorded in the Source table above. This packaging mirror does not publish independent parity benchmarks; validate on your target execution provider before production use.
Files
| File | Description |
|---|---|
enc.onnx | Encoder ONNX model |
erb_dec.onnx | ERB decoder ONNX model |
df_dec.onnx | Deep filtering decoder ONNX model |
Intended Use
Use these ONNX model files for speech enhancement and noise suppression experiments or integration work.
Training Data
Not documented in this repository. See the upstream DeepFilterNet project and paper for training details.
Evaluation
No repository-specific ONNX evaluation results are documented here.
Limitations
- DeepFilterNet usage examples commonly target 48 kHz audio; validate input requirements before deployment.
License
Apache-2.0. The upstream DeepFilterNet project is dual-licensed under MIT or Apache-2.0.
- Task
- Audio-to-Audio
- License
- apache-2.0
- Created
- May 21, 2026
- Updated
- Jun 15, 2026