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Resemble Enhance FP16 Quantized

FP16 (half-precision) quantized version of Resemble Enhance for mobile deployment.

ArtOtherBasismodellResembleAI/resemble-enhanceVersionRevision 6f635a1CBewertung

Modellquelle

Art
Other
Dateigröße
680 MB
Basismodell
ResembleAI/resemble-enhance
Version
vRevision 6f635a1
Aktualisiert
10. Okt. 2026
Downloads
0
Quelle
Hugging Face

Quellenbeschreibung

Resemble Enhance FP16 Quantized

FP16 (half-precision) quantized version of Resemble Enhance for mobile deployment.

Model Information

  • Original Model: ResembleAI/resemble-enhance
  • Quantization: FP16 (half precision)
  • Size Reduction: 50% (from FP32)
  • Parameters: 356,414,076
  • Model Size: 679.81 MB

Usage

This FP16 quantized model is optimized for:

  • iOS devices: Compatible with Apple Neural Engine (ANE)
  • Mobile deployment: Reduced memory footprint
  • Faster inference: 2-3x faster than FP32 on supported hardware

Loading the Model

import torch

# Load FP16 state dict
state_dict = torch.load("mp_rank_00_model_states_fp16.pt", map_location="cpu")

# Load into model (model must be converted to FP16 first)
model = YourResembleEnhanceModel()
model = model.half()  # Convert to FP16
model.load_state_dict(state_dict)
model.eval()

Conversion to CoreML (iOS)

For iOS deployment, convert to CoreML:

import coremltools as ct

# Convert PyTorch model to CoreML
mlmodel = ct.convert(
    model,
    inputs=[ct.TensorType(name="input", shape=input_shape)],
    minimum_deployment_target=ct.target.iOS16
)

# Save as .mlmodel
mlmodel.save("ResembleEnhanceFP16.mlmodel")

Performance

  • Size: 679.81 MB (50% reduction from FP32)
  • Inference Speed: 2-3x faster on Apple Neural Engine
  • Quality: Minimal perceptual loss compared to FP32

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.

Quellen

1 Quelle
Hugging FacePrimärVersion 6f635a158b09c9a770730de5241784ad210d2ea5
huggingface.co/aoiandroid/resemble-enhance-fp16-quantized/tree/6f635a158b09c9a770730de5241784ad210d2ea5

Verifiziert 14. Aug.

Modellartefakte

1 Artefakt

mp_rank_00_model_states_fp16.pt

pt · 680 MB · SHA-256 22d0b7481475…e4ae · Hugging Face

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Quellenauszüge

2 Auszüge

--- license: mit base_model: ResembleAI/resemble-enhance tags: - speech-enhancement - audio - quantization - fp16 - mobile - ios - apple-neural-engine pipeline_tag: audio-to-audio --- # Resemble Enhance FP16 Quantized FP16 (half-precision) quantized version of Resemble Enhance for mobile deployment. ## Model Information - **Original Model**: ResembleAI/resemble-enhance - **Quantization**: FP16 (half precision) - **Size Reduction**: 50% (from FP32) - **Parameters**: 356,414,076 - **Model Size**: 679.81 MB ## Usage This FP16 quantized model is optimized for: - **iOS devices**: Compatible with Apple Neural Engine (ANE) - **Mobile deployment**: Reduced memory footprint - **Faster inference**: 2-3x faster than FP32 on supported hardware ### Loading the Model ```python import torch # Load FP16 state dict state_dict = torch.load("mp_rank_00_model_states_fp16.pt", map_location="cpu") # Load into model (model must be converted to FP16 first) model = YourResembleEnhanceModel() model = model.half() # Convert to FP16 model.load_state_dict(state_dict) model.eval() ``` ## Conversion to CoreML (iOS) For iOS deployment, convert to CoreML: ```python import coremltools as ct # Convert PyTorch model to CoreML mlmodel = ct.convert( model, inputs=[ct.TensorType(name="input", shape=input_shape)], minimum_deployment_target=ct.target.iOS16 ) # Save as .mlmodel mlmodel.save("ResembleEnhanceFP16.mlmodel") ``` ## Performance - **Size**: 679.81 MB (50% reduction from FP32) - **Inference Speed**: 2-3x faster on Apple Neural Engine - **Quality**: Minimal perceptual loss compared to FP32 ## Original Model This is a quantized version of [ResembleAI/resemble-enhance](https://huggingface.co/ResembleAI/resemble-enhance). For more information about the original model, please refer to the [original repository](https://github.com/resemble-ai/resemble-enhance). ## License This model follows the same license as the original Resemble Enhance model.

Source context: 0 downloads · 0 likes · Pipeline audio-to-audio · Repo aoiandroid/resemble-enhance-fp16-quantized