31 lines
1.6 KiB
Markdown
31 lines
1.6 KiB
Markdown
# Vevo2 Voice Conversion on Athena
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This directory contains Athena's private Vevo2 voice-conversion studio.
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- Code: `open-mmlab/Amphion` commit
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`26f6883110181f1dbfe95c70a7c7dbaf4de5f42a` (MIT)
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- Weights: `RMSnow/Vevo2` (CC BY-NC-ND 4.0)
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- Runtime: PyTorch 2.7.1 + CUDA 12.8 inherited from Athena's tested audio
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separator image; the historical Amphion torch 2.0/cu118 pins are not used.
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- Storage: `/data/voice/vevo2`; removing that directory and the test image
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removes all downloaded artifacts.
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- Private UI: `http://192.168.1.212:8008` through WireGuard only.
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- Output: uncompressed mono WAV, 24 kHz.
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The 9 September technical gate converted the official 8.6-second speech sample
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through the production HTTP API in 2.342 seconds. A warm service start loaded
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the model in 12.216 seconds, and peak CUDA allocation during conversion was
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5605.6 MiB. The returned 24-kHz WAV was 412878 bytes and 8.6 seconds long. The
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service stores named reference voices, accepts a source clip, and returns a
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transient WAV download. Jobs and generated outputs are removed after delivery.
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It is deliberately not exposed on the university interface.
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The installed Compose project is named `mike-ai-voice`. Rebuild or recreate it
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with an explicit `VOICE_GPU_UUID` so Docker keeps the service attached to the
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RTX 5080. The profile controller starts and stops the existing container; it
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does not rebuild it during a mode switch.
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The weights are licensed CC BY-NC-ND 4.0. This deployment is for Mike's
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private, non-commercial use only. Do not use or expose it as a public or
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commercial voice-cloning service.
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