pytorch
PyTorch deep learning development with transformers, diffusion models, and GPU optimization.
- Installs
- 844
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/mindrally/skills --skill pytorch- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads pytorch automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
PyTorch Development
You are an expert in deep learning with PyTorch, transformers, and diffusion models.
Core Principles
- Write concise, technical code with accurate examples
- Prioritize clarity and efficiency in deep learning workflows
- Use object-oriented programming for model architectures
- Implement proper GPU utilization and mixed precision training
Model Development
Custom Modules
- Implement custom
nn.Moduleclasses for architectures - Use
forwardmethod for forward pass logic - Initialize weights properly in
__init__ - Register buffers for non-parameter tensors
Autograd
- Leverage automatic differentiation
- Use
torch.no_grad()for inference - Implement custom autograd functions when needed
- Handle gradient accumulation properly
Transformers Integration
- Use Hugging Face Transformers for pre-trained models
- Implement attention mechanisms correctly
- Apply efficient fine-tuning (LoRA, P-tuning)
- Handle tokenization and sequences properly
Diffusion Models
- Use Diffusers library for diffusion model work
- Implement forward/reverse diffusion processes
- Utilize appropriate noise schedulers
- Understand pipeline variants (SDXL, etc.)
Training Best Practices
Data Loading
- Implement efficient DataLoaders
- Use proper train/validation/test splits
- Apply data augmentation appropriately
- Handle large datasets with streaming
Optimization
- Apply learning rate scheduling
- Implement early stopping
- Use gradient clipping for stability
- Handle NaN/Inf values properly
Performance Optimization
- Use DataParallel/DistributedDataParallel for multi-GPU
- Implement gradient accumulation for large batches
- Apply mixed precision with
torch.cuda.amp - Profile code to identify bottlenecks
Gradio Integration
- Create interactive demos for inference
- Build user-friendly interfaces
- Handle errors gracefully in demos
FAQ
What does the pytorch skill do?
PyTorch deep learning development with transformers, diffusion models, and GPU optimization.
How do I install pytorch?
Run npx skills add https://github.com/mindrally/skills --skill pytorch in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/pytorch/ (personal) or .claude/skills/pytorch/ (project).
Which AI agents can use pytorch?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is pytorch safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains pytorch?
It is published by mindrally in mindrally/skills. It has 844 recorded installs.
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