Instructions to use thepatch/same-l-decoder-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Stable Audio 3
How to use thepatch/same-l-decoder-lora with Stable Audio 3:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Card: pair the depth result with a content-preservation measure
Browse files
README.md
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@@ -105,12 +105,19 @@ back through the autoencoder, which a continuation and a transform both do.
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Tonal frames (>12 dB tonality, 6β16 kHz) on 2-minute generations, mean of 4, the
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decoder adapter the only variable:
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| depth | stock | `squeakfix_v3` | |
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| d0 β fresh generation |
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| d1 β one transform or continuation |
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| d2 |
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| d3 |
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Same shape at fp16 serving precision, on two different DiT LoRAs, at 30 s and
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120 s. Because a transform and a continuation each re-encode their input,
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Tonal frames (>12 dB tonality, 6β16 kHz) on 2-minute generations, mean of 4, the
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decoder adapter the only variable:
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| depth | stock | `squeakfix_v3` | | 12β16 kHz | SI-SDR vs own d0 |
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| d0 β fresh generation | 364 | 422 | β16% | β5.6 β β5.3 | β |
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| d1 β one transform or continuation | 432 | 445 | β3% | β6.2 β β5.5 | 14.7 β 18.3 |
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| d2 | 821 | 519 | **37% fewer** | β6.6 β β5.6 | 10.1 β 13.7 |
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| d3 | 1665 | 619 | **63% fewer** | β7.1 β β5.8 | 7.8 β 11.2 |
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The last two columns are there because a tonal-frame count can fall for the wrong
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reason β an adapter that sands the top end posts a great count. This one does the
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opposite: at every depth it holds **more** 12β16 kHz energy than stock, sits
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marginally louder, and stays closer to its own depth-0 render, so it drifts less
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with depth rather than erasing what drifts. The band that drops is 8β12 kHz,
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where the artifact concentrates.
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Same shape at fp16 serving precision, on two different DiT LoRAs, at 30 s and
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120 s. Because a transform and a continuation each re-encode their input,
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