Push model using huggingface_hub.

README.md

@@ -1,57 +1,9 @@
 ---
-language:
-- en
-license: apache-2.0
 tags:
-- hearing loss
-- challenge
-- signal processing
-- source separation
-- audio
-- audio-to-audio
-- NonCausal
+- pytorch_model_hub_mixin
+- model_hub_mixin
 ---
 
-# Cadenza Challenge: CAD2-Task1
-
-A NonCausal Clarinet/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: false
-  * mask_nonlinear: relu
-  * norm_type: gLN
-* 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_Clarinet_NonCausal"
-).cpu()
-
-```
-
-        
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Library: [More Information Needed]
+- Docs: [More Information Needed]