fine-tuning
Fine-tuning pre-trained machine learning models for specific tasks using transfer learning techniques.
npx skills add majiayu000/claude-skill-registry --skill fine-tuning --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# fine-tuning ## Purpose This skill enables fine-tuning of pre-trained ML models using transfer learning, adapting them to specific tasks like text classification or image recognition. It leverages OpenClaw's AIMLOps framework to optimize training loops and resource usage. ## When to Use Use this skill when you have a pre-trained model (e.g., BERT for NLP) and a custom dataset that requires adaptation, such as sentiment analysis on domain-specific text. Apply it for tasks where training from scratch is inefficient, like in production environments with limited data. ## Key Capabilities - Fine-tune models with techniques like gradient checkpointing for memory efficiency. - Support for popular frameworks: Hugging Face Transformers, TensorFlow, and PyTorch. - Hyperparameter tuning via integrated tools, e.g., learning rate schedulers. - Distributed training across GPUs or cloud instances. - Model evaluation metrics like accuracy, F1-score, and loss tracking. ## Usage Patterns Start by preparing your dataset and model. Load data into a compatible format (e.g., JSONL for text), then invoke the fine-tuning command. Monitor progress via logs or callbacks. For pipelines, integrate as a step
- Purpose
- When to Use
- Key Capabilities
- Usage Patterns
- Common Commands/API
- Integration Notes
- Error Handling
- Concrete Usage Examples
- Graph Relationships
What does the fine-tuning skill do?
Fine-tuning pre-trained machine learning models for specific tasks using transfer learning techniques.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill fine-tuning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.