python-ml-deps
CommunityInstall ML Python deps with CUDA-aware setup.
Authorjayll1303
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Install ML libraries (PyTorch, Flash-Attention, DeepSpeed, bitsandbytes, xformers, RAPIDS, llama-cpp-python) with uv while avoiding CUDA/CuDNN driver conflicts and version mismatches across the stack.
Core Features & Use Cases
- Install ML libraries with CUDA-aware wheels and uv index configuration for reproducible, GPU-ready environments.
- Diagnose and resolve CUDA toolkit, driver, and cuDNN compatibility issues when building or deploying ML stacks.
- Prepare Python projects with pyproject.toml snippets and extras to pin CUDA-enabled dependencies.
Quick Start
Install ML dependencies with uv and CUDA-aware index URLs to set up a CUDA-enabled PyTorch workflow.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: python-ml-deps Download link: https://github.com/jayll1303/AIEKit/archive/main.zip#python-ml-deps Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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