II.
SkillArea overview
Reference · liveskill-area:ml-fine-tuning
ML Fine-Tuning overview
Adapting pretrained foundation models: full fine-tuning, parameter- efficient methods (LoRA, QLoRA, IA3, prefix tuning), instruction tuning, RLHF / DPO, dataset curation, and eval harnesses.
Attributes
displayName
ML Fine-Tuning
description
Adapting pretrained foundation models: full fine-tuning, parameter-
efficient methods (LoRA, QLoRA, IA3, prefix tuning), instruction
tuning, RLHF / DPO, dataset curation, and eval harnesses.
domains
requiresLanguages
expertiseLevels
- intermediate
- expert
- authoritative
Outgoing edges
applies_to2
- domain:ml-ops·DomainMLOps
- specialization:llm-fine-tuning·SpecializationLLM Fine-tuning
uses_language2
- language:python·LanguagePython
- language:python·LanguagePython
Incoming edges
covers1
- benchmark:re-bench·BenchmarkRE-Bench
lib_requires_skill_area4
- lib-agent:ai-agents-conversational--fine-tuning-specialist·LibraryAgentfine-tuning-specialist
- lib-skill:ai-agents-conversational--huggingface-classifier·LibrarySkillhuggingface-classifier
- lib-skill:ai-agents-conversational--rasa-nlu-integration·LibrarySkillrasa-nlu-integration
- lib-skill:ai-agents-conversational--setfit-few-shot·LibrarySkillsetfit-few-shot
prerequisite_for_learning2
- skill-area:machine-learning·SkillAreaMachine Learning
- skill-area:synthetic-data-generation·SkillAreaSynthetic Data Generation
requires_expertise4
- role:quantitative-analyst·RoleQuantitative Analyst
- role:research-analyst·RoleResearch Analyst
- role:ml-engineer·RoleMachine Learning Engineer
- role:ml-engineer-convergent·RoleML Engineer
requires_skill_area29
- stack-profile:llm-fine-tuning·StackProfileLLM Fine-Tuning Stack (PyTorch, HuggingFace, PEFT/LoRA, W&B, vLLM)
- workflow:crop-yield-forecasting·WorkflowCrop Yield Forecasting
- workflow:momentum-signal-research·WorkflowMomentum Signal Research
- workflow:ai-powered-product-feature-review·WorkflowAI-Powered Product Feature Review
- workflow:model-fairness-audit·WorkflowModel Fairness Audit
- workflow:model-explainability-review·WorkflowModel Explainability Review
- workflow:dataset-versioning-governance·WorkflowDataset Versioning Governance
- workflow:ml-model-versioning-governance·WorkflowML Model Versioning Governance
- workflow:adaptive-learning-model-review·WorkflowAdaptive Learning Model Review
- workflow:renewable-energy-forecasting·WorkflowRenewable Energy Forecasting
- workflow:model-risk-management-review·WorkflowModel Risk Management Review
- workflow:anti-cheat-system-audit·WorkflowAnti-Cheat System Audit
- workflow:underwriting-model-validation·WorkflowUnderwriting Model Validation
- workflow:material-characterization-pipeline·WorkflowMaterial Characterization Pipeline
- workflow:model-training-cycle·WorkflowModel Training Cycle
- workflow:model-deployment-pipeline·WorkflowModel Deployment Pipeline
- workflow:model-monitoring-drift-detection·WorkflowModel Monitoring and Drift Detection
- workflow:hyperparameter-tuning-cycle·WorkflowHyperparameter Tuning Cycle
- workflow:data-labeling-pipeline·WorkflowData Labeling Pipeline
- workflow:model-card-maintenance·WorkflowModel Card Maintenance
- workflow:ml-experiment-tracking·WorkflowML Experiment Tracking
- workflow:nano-characterization-pipeline·WorkflowNano-Characterization Pipeline
- workflow:alpha-factor-research-cycle·WorkflowAlpha Factor Research Cycle
- workflow:bioinformatics-pipeline-validation·WorkflowBioinformatics Pipeline Validation
- workflow:experiment-reproducibility-review·WorkflowExperiment Reproducibility Review
- workflow:athlete-performance-analytics-review·WorkflowAthlete Performance Analytics Review
- workflow:fraud-detection-model-review·WorkflowFraud Detection Model Review
- workflow:actuarial-model-validation·WorkflowActuarial Model Validation
- workflow:legal-ai-bias-audit·WorkflowLegal AI Bias Audit
used_by_skill_area1
- language:python·LanguagePython