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@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+diffusion_head.pt2 filter=lfs diff=lfs merge=lfs -text
+ssl_encoder.pt2 filter=lfs diff=lfs merge=lfs -text
+vae_decoder.pt2 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,20 @@
+---
+license: cc-by-nc-4.0
+---
+
+# DialogueSidon
+
+Two-speaker dialogue separation model based on diffusion with a VAE-32 latent space.
+
+## Components
+
+| File | Description |
+|---|---|
+| `ssl_encoder.pt2` | w2v-BERT 2.0 backbone + latent projection heads |
+| `diffusion_head.pt2` | DiffusionTransformerHead — single denoising step |
+| `vae_decoder.pt2` | DAC VAE decoder: latents → 24 kHz audio |
+| `metadata.json` | Latent normalisation stats, scheduler config, model dims |
+
+## Usage
+
+Load with `torch.export.load()`. The diffusion sampling loop and fbank feature extraction remain in Python.

diffusion_head.pt2

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metadata.json

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+      "thresholding",
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+      "beta_start",
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+    ]
+  }
+}

ssl_encoder.pt2

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vae_decoder.pt2

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