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ConvTasNet_Cello_Causal
cadenzachallenge/ConvTasNet_Cello_Causal
ConvTasNet_Cello_Causal is a audio-to-audio model from cadenzachallenge. Use it for the audio-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
A Causal Cello/Others separation model for the CAD2-Task2 baseline system.
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At a glance
- Task
- Audio-to-Audio
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jul 16, 2024
- Updated
- Jul 16, 2024
- SHA
- 61d613c8
Model card
From the Hugging Face model README
Cadenza Challenge: CAD2-Task1
A Causal Cello/Others separation model for the CAD2-Task2 baseline system.
- Architecture: ConvTasNet (Kaituo XU) with multichannel support (Alexandre Defossez).
- Parameters:
- B: 256
- C: 2
- H: 512
- L: 20
- N: 256
- P: 3
- R: 3
- X: 8
- audio_channels: 2
- causal: true
- mask_nonlinear: relu
- norm_type: cLN
- training:
- sample_rate: 44100
- samples_per_track: 64
- segment: 5.0
- aggregate: 2
- batch_size: 4
- early_stop: true
- epochs: 200
Dataset
The model was trained using EnsembleSet and CadenzaWoodwind datasets.
How to use
from tasnet import ConvTasNetStereo
model = ConvTasNetStereo.from_pretrained(
"cadenzachallenge/ConvTasNet_Cello_Causal"
).cpu()
- Task
- Audio-to-Audio
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Jul 16, 2024
- Updated
- Jul 16, 2024