Ai Ml
- Updated May 7, 2026
- CHENyiru3/AI-Skills-Collections
ai-ml is an agent skill that packages PyTorch, HuggingFace, PEFT, TRL, and DeepSpeed-oriented training utilities for coding agents.
About
The ai-ml entry in CHENyiru3’s AI-Skills-Collections is a curated skills-market bundle for developers who ship ML features with coding agents. It groups procedural knowledge around PyTorch, HuggingFace Transformers, parameter-efficient fine-tuning (PEFT), reinforcement-style training helpers (TRL), and distributed training utilities (DeepSpeed), plus nested skills like minimax-cli for LLM CLI workflows. Install or reference this bundle when you are past idea-stage validation and actively building or iterating on models, datasets, or inference pipelines—not when you only need a marketing landing page. It fits developers who already use agent skills for repo work and want the same pattern for training scripts, config, and HF ecosystem tasks. Prism lists it as a facetable package under AI verticals so you can discover related agent skills alongside integrations and checkers.
- Covers PyTorch, Transformers, HuggingFace, PEFT, TRL, and DeepSpeed training patterns
- Market bundle includes LLM tooling such as minimax-cli under the ai-ml path
- Aimed at fine-tuning, efficient training, and HuggingFace-centric workflows
- Collection entry in AI-Skills-Collections skills-market (non-strict bundle)
- Use when you want agent-guided ML setup instead of ad-hoc notebook-only work
Ai Ml by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
/plugin marketplace add CHENyiru3/AI-Skills-Collections/plugin install ai-ml@ai-skillsAdd your badge
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| Last updated | May 7, 2026 |
|---|---|
| Repository | CHENyiru3/AI-Skills-Collections ↗ |
What it does
Bundle AI/ML agent capabilities—PyTorch, HuggingFace, PEFT, TRL, DeepSpeed, and LLM CLI helpers—for fine-tuning, training workflows, and model ops from your coding agent.
Who is it for?
Best when you're shipping ML features and already use Claude Code, Cursor, or Codex and want HF-centric training skills in one market path.
Skip if: Skip if you only need a no-code demo, or projects with zero Python/GPU training needs.
When should I use this skill?
You are implementing or maintaining ML training, fine-tuning, or HuggingFace/PyTorch utilities with an agent.
What you get
Your agent follows collection-backed ML workflows for training setup and LLM CLI tasks instead of guessing framework conventions.
- Training or fine-tune scripts and configs
- Agent-ready steps for nested LLM CLI skills
- Documented ML workflow aligned to bundle paths
Files
AI/ML — PyTorch, Transformers, HuggingFace, PEFT, TRL, DeepSpeed, training utilities
ai-ml
Source: ./skills-market/ai-ml
{ "name": "ai-ml", "skills": [ "./ai-ml/llm/minimax-cli" ], "source": "./skills-market/ai-ml", "strict": false, "description": "AI/ML — PyTorch, Transformers, HuggingFace, PEFT, TRL, DeepSpeed, training utilities" }
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Use this skills-market bundle for procedural ML training knowledge—not as a hosted MCP server or a generic productivity planner.
FAQ
Who is ai-ml for?
Developers building or maintaining ML models with PyTorch and HuggingFace who want agent skills instead of only static docs.
When should I use ai-ml?
During Validate when you prototype a model pipeline, in Build when you implement fine-tuning and training scripts, and in Operate when you iterate on checkpoints and training configs—with agent assistance.
Is ai-ml safe to install?
Review the Security Audits panel on this Prism page and inspect each nested skill’s permissions before granting shell, network, or GPU-related access.