groadabike
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Push model using huggingface_hub.
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README.md
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---
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language:
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- en
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license: apache-2.0
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tags:
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- signal processing
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- source separation
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- audio
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- audio-to-audio
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- NonCausal
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#
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* Architecture: ConvTasNet (Kaituo XU) with multichannel support (Alexandre Defossez).
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* Parameters:
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* B: 256
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* C: 2
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* H: 512
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* L: 20
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* N: 256
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* P: 3
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* R: 3
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* X: 8
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* audio_channels: 2
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* causal: false
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* mask_nonlinear: relu
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* norm_type: gLN
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* training:
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* sample_rate: 44100
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* samples_per_track: 64
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* segment: 5.0
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* aggregate: 2
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* batch_size: 4
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* early_stop: true
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* epochs: 200
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## Dataset
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The model was trained using EnsembleSet and CadenzaWoodwind datasets.
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## How to use
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```
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from tasnet import ConvTasNetStereo
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model = ConvTasNetStereo.from_pretrained(
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"cadenzachallenge/ConvTasNet_Flute_NonCausal"
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).cpu()
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```
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---
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tags:
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- pytorch_model_hub_mixin
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- model_hub_mixin
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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- Library: [More Information Needed]
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- Docs: [More Information Needed]
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