Instructions to use mochiexists528/ace-step-mlx-weights-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mochiexists528/ace-step-mlx-weights-xl with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir ace-step-mlx-weights-xl mochiexists528/ace-step-mlx-weights-xl
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
ACE-Step MLX Weights XL (fp16)
MLX-compatible fp16 package for ACE-Step 1.5 XL-turbo. This repo follows the
same layout as mochiexists528/ace-step-mlx-weights, with the XL-turbo DiT
under dit/ and the shared text encoder, VAE, and tokenizer under their usual
directories.
Contents
text_encoder/ Qwen3-Embedding-0.6B text encoder
dit/ ACE-Step v1.5 XL-turbo DiT + silence latent
vae/ ACE-Step Oobleck VAE decoder
tokenizer/ Qwen3 tokenizer files
Phase 6 LM-Conditioning
Phase 6 is optional. Baseline XL generation only needs the text encoder, DiT,
VAE, tokenizer, and silence latent files above. To enable Phase 6
LM-conditioning, pass a shared planner snapshot with --lm-weights.
The recommended planner repos are:
mochiexists528/ace-step-mlx-planner-1.7b-q4for lower storage and memory usemochiexists528/ace-step-mlx-planner-1.7bfor fp16 desktop/reference runs
The fp16 XL DiT carries the FSQ projection and AudioTokenDetokenizer tensors
inline in dit/model.safetensors, so it does not need a separate
detokenizer.safetensors conditioning sidecar.
Source Attribution
This is a derivative repack of upstream ACE-Step and Qwen artifacts for MLX. The XL-turbo DiT and VAE come from ACE-Step 1.5. The text encoder, tokenizer, and planner base family come from Qwen3. Planner weights are packaged in the shared Phase 6 planner repos listed above, not duplicated in this model repo. Tensor names and architecture are not changed; upstream bfloat16 tensors are stored as fp16 for MLX safetensors compatibility.
Quantized