aoiandroid/resemble-enhance-int8-quantized

Resemble Enhance INT8 Quantized

INT8 (8-bit integer) quantized version of Resemble Enhance for mobile deployment.

Model Information

• Original Model: ResembleAI/resemble-enhance
• Quantization: INT8 (8-bit integer)
• Size Reduction: 75% (from FP32)
• Parameters: 356,414,076
• Model Size: 339.90 MB

Usage

This INT8 quantized model is optimized for:

• Android devices: Optimized for mobile CPUs
• Edge devices: Maximum memory efficiency
• Low-power devices: Reduced computational requirements

Loading the Model

import torch

# Load INT8 state dict
state_dict = torch.load("mp_rank_00_model_states_int8.pt", map_location="cpu")

# Note: INT8 quantized models require special handling
# Use torch.quantization utilities for proper loading

Conversion to TFLite (Android)

For Android deployment, convert to TensorFlow Lite:

import torch

# Convert PyTorch to ONNX first
torch.onnx.export(model, dummy_input, "model.onnx")

# Then convert ONNX to TFLite using appropriate tools

Performance

• Size: 339.90 MB (75% reduction from FP32)
• Inference Speed: 3-4x faster on mobile CPUs
• Memory: 4x less memory than FP32
• Quality: Minimal perceptual loss for most use cases

Original Model

This is a quantized version of ResembleAI/resemble-enhance.

For more information about the original model, please refer to the original repository.

License

This model follows the same license as the original Resemble Enhance model.