Resemble Enhance FP16 Quantized
FP16 (half-precision) quantized version of Resemble Enhance for mobile deployment.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 680 MB
- Modelo base
- ResembleAI/resemble-enhance
- Versión
- vRevision 6f635a1
- Actualizado
- 10 oct 2026
- Descargas
- 0
- Fuente
- Hugging Face
Descripción de la fuente
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.
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 14 ago
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- 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
