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@@ -13,11 +13,9 @@ base_model: ACE-Step/ACE-Step1.5
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  4-bit quantized MLX weights for [ACE-Step/ACE-Step1.5](https://huggingface.co/ACE-Step/ACE-Step1.5).
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- Converted and quantized using [mlx-audio](https://github.com/Blaizzy/mlx-audio).
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-
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  - Decoder and encoder quantized to 4-bit (group_size=64)
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  - VAE, tokenizer, and detokenizer kept in full precision
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- - **2.2GB** main model (vs 9.6GB fp32) + 0.7GB VAE + 2.4GB text encoder
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  ## Usage
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@@ -34,6 +32,24 @@ for result in model.generate(
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  sample_rate = result.sample_rate
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  ```
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  The model uses a 5Hz Language Model planner by default (`use_lm=True`) which generates
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- a song blueprint before running the diffusion transformer. This is required for the
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- turbo model to produce music.
 
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  4-bit quantized MLX weights for [ACE-Step/ACE-Step1.5](https://huggingface.co/ACE-Step/ACE-Step1.5).
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  - Decoder and encoder quantized to 4-bit (group_size=64)
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  - VAE, tokenizer, and detokenizer kept in full precision
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+ - **2.2GB** main model + 0.7GB VAE + 2.4GB text encoder
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  ## Usage
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  sample_rate = result.sample_rate
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  ```
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+ ## With Vocals
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+
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+ ```python
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+ for result in model.generate(
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+ text="English pop song with clear female vocals, catchy melody",
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+ lyrics="""[verse]
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+ Dance with me tonight
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+ Under the neon lights
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+
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+ [chorus]
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+ We're alive, we're on fire
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+ Dancing higher and higher
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+ """,
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+ duration=60.0,
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+ vocal_language="en",
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+ ):
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+ ...
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+ ```
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+
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  The model uses a 5Hz Language Model planner by default (`use_lm=True`) which generates
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+ a song blueprint before running the diffusion transformer.