MindIE Stable Diffusion inference engine for Ascend NPUs
Project description
MindIE SD
MindIE SD is an Ascend-focused inference acceleration toolkit for Stable Diffusion and related multimodal generation workloads.
Highlights
- Ascend-friendly custom operators and fused kernels
- Quantization, sparse quantization, cache, and parallel execution features
torch.compileintegration for graph-level acceleration
Quick start
Complete the environment preparation and MindIE SD installation first, then install model-specific dependencies and run an example:
git clone https://modelers.cn/MindIE/Wan2.1.git
cd Wan2.1
pip install -r requirements.txt
Documentation
- English overview: docs/en/README.md
- English quick start: docs/en/quick_start.md
- English installation guide: docs/en/installing_guide.md
- English user guide: docs/en/menu_user_manual.md
- English architecture: docs/en/architecture.md
- English environment variables: docs/en/environment_variable_configuration.md
- English support matrix: docs/en/features/supported_matrix.md
- English cache features: docs/en/features/cache.md
- English parallelism features: docs/en/features/parallelism.md
- English sparse quantization: docs/en/features/sparse_quantization.md
- Chinese overview: docs/zh/index.md
- Chinese quick start: docs/zh/quick_start.md
- Chinese installation guide: docs/zh/installing_guide.md
- Chinese architecture: docs/zh/architecture.md
Community and governance
- Contributing: contributing.md
- Code of conduct: CODE_OF_CONDUCT.md
- Governance: docs/en/community/governance.md
Project details
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