Provide implementations of advanced data structures
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
FreePublished on GitHub
spacy-ner
spaCy NER model training and entity extraction for conversational AI
The English summary is being prepared. Showing the original description.
See how to installFiles included (2)
- SKILL.md1.5 KB
- README.md425 B
SKILL.md (original)
Review the instructions the agent will receive before you install.
spaCy NER Skill
Capabilities
- Train custom spaCy NER models
- Configure entity extraction pipelines
- Design annotation schemas
- Implement entity linking
- Set up model evaluation
- Deploy efficient NER inference
Target Processes
- entity-extraction-slot-filling
- chatbot-design-implementation
Implementation Details
spaCy Components
- NER: Named Entity Recognition
- EntityLinker: Link to knowledge bases
- EntityRuler: Rule-based matching
- SpanCategorizer: Overlapping entities
Training Configuration
- config.cfg setup
- Training data format (spaCy v3)
- Augmentation strategies
- Evaluation metrics
Configuration Options
- Base model selection (en_core_web_*)
- Custom entity types
- Training parameters
- GPU acceleration
- Model packaging
Best Practices
- Quality annotation data
- Balance entity types
- Use prodigy for annotation
- Regular model evaluation
Dependencies
- spacy
- spacy-transformers (optional)
Reviews
No reviews yet. Tell others what you thought.
Comments
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
More skills from this repository
Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
agent-booster
FreeWASM-based instant code transforms for simple tasks, achieving 352x speedup over LLM inference with zero cost.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
Generate visual representations of algorithm execution
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
anti-drift
FreeHierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026