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0ed6b0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | # Installing Dependencies
Install from source (recommended):
```
git clone https://github.com/modelscope/DiffSynth-Studio.git
cd DiffSynth-Studio
pip install -e .
```
Install from PyPI (there may be delays in version updates; for latest features, install from source):
```
pip install diffsynth
```
To keep the framework lightweight, the base installation only installs the necessary dependencies. We provide some additional installation options:
* `[audio]`: Support for audio models, e.g., ACE-Step, MiniMax-Music3, etc.
* `[quant]`: For parameter quantization, enabling precisions such as NF4, INT8, NVFP4.
* `[training]`: For distributed large-scale pretraining.
* `[logger]`: To enable training loggers such as TensorBoard, SwanLab, etc.
* `[npu]`: For Ascend NPU devices with x86 architecture.
* `[npu_aarch64]`: For Ascend NPU devices with aarch64/ARM architecture.
* Dependencies of specific models
* `[infiniteyou]`: https://arxiv.org/abs/2503.16418
* `[ses]`: https://arxiv.org/abs/2602.03208
* `[nexusgen]`: https://arxiv.org/pdf/2504.21356
* `[all]`: Includes all dependencies except the "dependencies of specific models" above.
You can install multiple sets of dependencies with `pip install -e ".[audio,quant]"` or `pip install diffsynth[audio,quant]`.
## GPU/NPU Support
### NVIDIA GPU
Install as described above.
### AMD GPU
You need to install the `torch` package with ROCm support. Taking ROCm 6.4 (as of the article update date: December 15, 2025) on Linux as an example, run the following command:
```shell
pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm6.4
```
### Apple Silicon
On Apple Silicon devices, no changes to the installation steps are needed. However, since VRAM and memory are unified, replace all `"cuda"` in the code with `"mps"` or `"cpu"`.
### Ascend NPU
1. Install [CANN](https://www.hiascend.com/document/detail/zh/canncommercial/83RC1/softwareinst/instg/instg_quick.html?Mode=PmIns&InstallType=local&OS=openEuler&Software=cannToolKit) through official documentation.
2. Install from source
```shell
git clone https://github.com/modelscope/DiffSynth-Studio.git
cd DiffSynth-Studio
# aarch64/ARM
pip install -e .[npu_aarch64]
# x86
pip install -e .[npu] --extra-index-url "https://download.pytorch.org/whl/cpu"
```
When using Ascend NPU, please replace `"cuda"` with `"npu"` in your Python code. For details, see [NPU Support](../Pipeline_Usage/GPU_support.md#ascend-npu).
## Other Installation Issues
If you encounter issues during installation, they may be caused by upstream dependencies. Please refer to the documentation for these packages:
* [torch](https://pytorch.org/get-started/locally/)
* [Ascend/pytorch](https://github.com/Ascend/pytorch)
* [sentencepiece](https://github.com/google/sentencepiece)
* [cmake](https://cmake.org)
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