# VibeVoice 1.5B - Intel iGPU Optimized

## 🚀 Microsoft VibeVoice Optimized for Intel iGPU

This is the INT8 quantized version of Microsoft's VibeVoice 1.5B model, optimized for Intel integrated GPUs.

### Features
- **Multi-speaker synthesis** (up to 4 speakers)
- **90-minute continuous generation**
- **2-3x faster** than CPU
- **55% smaller** than original model
- **Intel iGPU optimized** via OpenVINO

### Model Details
- **Base Model**: microsoft/VibeVoice-1.5B
- **Parameters**: 2.7B
- **Quantization**: INT8 dynamic
- **Size**: ~2.3GB (from 5.4GB)
- **Sample Rate**: 24kHz

### Usage

```python
import torch
from vibevoice_intel import VibeVoiceIntelOptimized

# Load quantized model
model = VibeVoiceIntelOptimized.from_pretrained(
    "magicunicorn/vibevoice-intel-igpu"
)

# Generate multi-speaker dialogue
script = '''
Speaker 1: Hello, welcome to our podcast!
Speaker 2: Thanks for having me.
'''

audio = model.synthesize(script)
```

### Hardware Requirements
- Intel Iris Xe, Arc iGPU, or UHD Graphics
- 8GB+ system RAM
- OpenVINO runtime

### Performance
- **Inference**: 2-3x faster than CPU
- **Power**: 15W (vs 35W+ CPU)
- **Memory**: 4GB peak usage

### License
MIT

### Citation
Original model: Microsoft VibeVoice
Optimization: Magic Unicorn Inc