ugh
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@ -27,6 +27,7 @@ models:
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interleave: False # interleaves RVQ levels, only works with above for now
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interleave: False # interleaves RVQ levels, only works with above for now
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audio_embedding_mode: "" # "" | "inclusive" | "exclusive", whether to utilize the audio backend's embeddings with the input embeddings
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audio_embedding_mode: "" # "" | "inclusive" | "exclusive", whether to utilize the audio backend's embeddings with the input embeddings
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audio_embedding_sums: False # whether the input embeddings include all prior RVQ levels (sums) or only the current one, further experimentation is needed to see if this matters
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audio_embedding_sums: False # whether the input embeddings include all prior RVQ levels (sums) or only the current one, further experimentation is needed to see if this matters
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p_rvq_levels: "equal" # "equal" | "auto", sets probabilities of which RVQ level to select during training, auto will have the next RVQ level half as likely as the previous one
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hyperparameters:
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hyperparameters:
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autotune: False
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autotune: False
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@ -262,11 +262,7 @@ class Model:
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if cfg.optimizations.bitnet:
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if cfg.optimizations.bitnet:
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name.append("bitnet")
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name.append("bitnet")
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if self.interleave:
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name.append(f'{self.resp_levels}')
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name.append("interleaved")
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else:
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name.append(f'{self.prom_levels}')
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return "-".join(name)
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return "-".join(name)
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