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@@ -54,17 +54,6 @@ RUN pip install --no-cache-dir "git+https://github.com/Tencent-Hunyuan/AuK.git@$
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# ChatML turn; soundfile writes the generated wavs and the prompt clips stage 3 scores SIM on.
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RUN pip install --no-cache-dir "datasets<4.0" tqdm soundfile librosa
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# Bake the weights into the image so a job never spends its GPU time downloading ~20 GB:
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# * tencent/AuK 1.5B base (MIT, ungated) -> /opt/models/AuK
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# * tencent/AuK-Flash distilled 4-step (MIT, ungated) -> /opt/models/AuK-Flash
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# * Qwen/Qwen2.5-Omni-3B the text/audio encoder both checkpoints load at runtime
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# Each AuK release dir carries its own config.yaml + vae.safetensors, which AukInfer picks up
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# from next to the checkpoint. run_eval.py reads them via --checkpoint_dir / --qwen_dir and falls
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# back to a Hub snapshot if a dir is missing, so dropping any of these only costs download time.
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RUN python3 -c "from huggingface_hub import snapshot_download; snapshot_download('tencent/AuK', local_dir='/opt/models/AuK')"
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RUN python3 -c "from huggingface_hub import snapshot_download; snapshot_download('tencent/AuK-Flash', local_dir='/opt/models/AuK-Flash')"
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RUN python3 -c "from huggingface_hub import snapshot_download; snapshot_download('Qwen/Qwen2.5-Omni-3B', local_dir='/opt/models/Qwen2.5-Omni-3B')"
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# Copy the full repository
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COPY . /app
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# ChatML turn; soundfile writes the generated wavs and the prompt clips stage 3 scores SIM on.
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RUN pip install --no-cache-dir "datasets<4.0" tqdm soundfile librosa
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# Copy the full repository
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COPY . /app
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