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README.md
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---
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license: mit
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tags:
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- audio
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- audio-super-resolution
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- upscaling
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- audiosr
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- safetensors
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- maestraea
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pipeline_tag: audio-to-audio
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---
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# AudioSR Models (Safetensors)
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**Audio Super-Resolution — Upscale Any Audio to 48kHz**
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[Original Source](https://github.com/haoheliu/versatile_audio_super_resolution) by [Haohe Liu](https://github.com/haoheliu) · MIT License
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> Converted from `pytorch_model.bin` to safetensors format for faster loading and safer deserialization. For use with [Mæstræa AI Workstation](https://github.com/AEmotionStudio/Maestraea).
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## Available Models
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| Variant | Files | Size | Description |
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|---------|-------|------|-------------|
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| **basic** | `basic/audiosr_basic.safetensors` | 6.2 GB | General audio (music, SFX, speech) |
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| **speech** | `speech/audiosr_speech-*.safetensors` (3 shards) | 6.2 GB | Optimized for spoken word |
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## What AudioSR Does
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AudioSR uses latent diffusion to upscale any audio to 48kHz, restoring high-frequency content that was lost to:
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- Low sample rate recording (8kHz, 16kHz, 22kHz → 48kHz)
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- Lossy compression (MP3, AAC artifacts)
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- Bandwidth-limited audio
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### Key Parameters
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| Parameter | Range | Default | Description |
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|-----------|-------|---------|-------------|
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| `ddim_steps` | 10–200 | 50 | More steps = higher quality |
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| `guidance_scale` | 1–10 | 3.5 | Prompt adherence |
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| `model_name` | basic/speech | basic | Which variant to use |
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### VRAM Requirements
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- **Minimum**: ~4 GB
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- **Recommended**: ~6 GB (for longer audio)
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## Usage with Mæstræa
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These models are automatically downloaded by the Mæstræa AI Workstation backend.
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### Direct Usage
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```python
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import audiosr
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model = audiosr.build_model(model_name="basic")
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waveform = audiosr.super_resolution(
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model, "input.wav",
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seed=42, guidance_scale=3.5, ddim_steps=50
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)
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```
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## Original Source
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| Variant | Original Repo |
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|---------|--------------|
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| basic | [haoheliu/audiosr_basic](https://huggingface.co/haoheliu/audiosr_basic) |
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| speech | [haoheliu/audiosr_speech](https://huggingface.co/haoheliu/audiosr_speech) |
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## License
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MIT — same as the original AudioSR release.
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## Credits
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- **Model**: [AudioSR](https://github.com/haoheliu/versatile_audio_super_resolution) by Haohe Liu et al.
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- **Paper**: [Versatile Audio Super Resolution](https://arxiv.org/abs/2309.07314)
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- **Conversion & Mirror by**: [AEmotionStudio](https://huggingface.co/AEmotionStudio)
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