Update README.md

README.md

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-license: cc0-1.0
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+---
+license: cc0-1.0
+---
+
+🚀 **AEROMamba: Efficient Audio Super-Resolution**  
+*AI-Generated README - Original: [GitHub](https://github.com/aeromamba-super-resolution/aeromamba) | [Demo](https://aeromamba-super-resolution.github.io/)*
+
+---
+
+## Model Overview
+**Architecture**: Hybrid GAN + Mamba SSM  
+**Task**: 11.025 kHz → 44.1 kHz audio upsampling  
+**Key Improvements**:
+- 14x faster inference vs AERO
+- 5x less GPU memory usage
+- 66.47 subjective score (vs AERO's 60.03)
+
+**Checkpoint**: [MUSDB18-HQ Model](https://huggingface.co/KingNish/AEROMamba/blob/main/checkpoint.th)
+
+---
+
+## Quick Start
+```python
+# Installation
+pip install torch==1.12.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
+pip install causal-conv1d==1.1.2 mamba-ssm==1.1.3
+
+# Inference
+from src.models.aeromamba import AEROMamba
+import torchaudio
+
+model = AEROMamba.load_from_checkpoint("checkpoint.th")
+lr_audio, sr = torchaudio.load("low_res.wav")  # 11kHz input
+hr_audio = model(lr_audio)  # 44.1kHz output
+```
+
+---
+
+## Performance (MUSDB18)
+| Metric          | Low-Res | AERO  | AEROMamba |
+|-----------------|---------|-------|-----------|
+| ViSQOL ↑        | 1.82    | 2.90  | **2.93**  |
+| LSD ↓           | 3.98    | 1.34  | **1.23**  |
+| Subjective ↑    | 38.22   | 60.03 | **66.47** |
+
+**Hardware**: 14x faster on RTX 3090 (0.087s vs 1.246s)
+
+---
+
+## Training Data
+**MUSDB18-HQ**:
+- 150 full-track music recordings
+- 44.1 kHz originals → 11.025 kHz downsampled pairs
+- 87.5/12.5 train-val split
+
+---
+
+## Citation
+```bibtex
+@inproceedings{Abreu2024lamir,
+  author    = {Wallace Abreu and Luiz Wagner Pereira Biscainho},
+  title     = {AEROMamba: Efficient Audio SR with GANs and SSMs},
+  booktitle = {Proc. Latin American Music IR Workshop},
+  year      = {2024}
+}
+```
+
+*This README was AI-generated based on original project materials. For training code and OLA inference scripts, visit the [GitHub repo](https://github.com/aeromamba-super-resolution/aeromamba).*