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VibeVoice 1.5B - Intel iGPU Optimized
π 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
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
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