Instructions to use kingfang008/step-audio-editx-4bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use kingfang008/step-audio-editx-4bit-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir step-audio-editx-4bit-mlx kingfang008/step-audio-editx-4bit-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| license: apache-2.0 | |
| library_name: mlx | |
| tags: | |
| - mlx | |
| - mlx-speech | |
| - tts | |
| - voice-cloning | |
| - audio-editing | |
| - apple-silicon | |
| base_model: stepfun-ai/Step-Audio-EditX | |
| # Step-Audio-EditX — MLX 4-bit | |
| Self-contained **affine 4-bit MLX** bundle of [Step-Audio-EditX](https://huggingface.co/stepfun-ai/Step-Audio-EditX) for Apple Silicon. | |
| This is **not** the CUDA/vLLM checkpoint [`stepfun-ai/Step-Audio-EditX-AWQ-4bit`](https://huggingface.co/stepfun-ai/Step-Audio-EditX-AWQ-4bit). Load it with [mlx-speech](https://github.com/appautomaton/mlx-speech). | |
| Converted from [`appautomaton/step-audio-editx-8bit-mlx`](https://huggingface.co/appautomaton/step-audio-editx-8bit-mlx) using MLX affine quantization (`bits=4`, `group_size=64`, `mode=affine`). | |
| | Component | Precision | | |
| | --- | --- | | |
| | Step1 LM, flow-model, VQ02 | affine int4 | | |
| | VQ06, HiFT, CampPlus, flow conditioner | bf16 (unchanged) | | |
| Total size ≈ **2.53 GB** (upstream int8 ≈ 4.4 GB). | |
| ## Use | |
| ```bash | |
| pip install mlx-speech | |
| hf download kingfang008/step-audio-editx-4bit-mlx --local-dir ./step-audio-editx-4bit-mlx | |
| mlx-speech tts \ | |
| --model ./step-audio-editx-4bit-mlx \ | |
| --reference-audio reference.wav \ | |
| --reference-text "Transcript of the reference audio." \ | |
| --text "New cloned speech." \ | |
| -o output.wav | |
| ``` | |
| Requires an Apple Silicon Mac (M1 or later). | |