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README.md

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-tags:
-- pytorch_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:
-- Library: [More Information Needed]
-- Docs: [More Information Needed]
+        ---
+        license: apache-2.0
+        language:
+        - en
+        tags:
+        - hearing loss
+        - challenge
+        - signal processing
+        - source separation
+        - audio
+        - audio-to-audio
+        - Causal
+        ---
+
+        # Cadenza Challenge: CAD2-Task1
+
+        A Causal separation model for the CAD2-Task2 system.
+
+        This model is an ensemble of the following instruments:
+            - Bassoon
+            - Cello
+            - Clarinet
+            - Flute
+            - Oboe
+            - Sax
+            - Viola
+            - Violin
+        Each model is based on the 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
+
+        ## Dataset
+        The model was trained using EnsembleSet and CadenzaWoodwind datasets.
+
+        ## How to use
+
+        ```
+        from dynamic_source_separator import DynamicSourceSeparator
+
+        model = DynamicSourceSeparator.from_pretrained(
+            "cadenzachallenge/Dynamic_Source_Separator_Causal"
+        ).cpu()
+
+        ```
+
+