ML Model Lifecycle
curated by SkillMD · plugin · 10 skills
Train, evaluate, and deploy a production ML system with monitoring.
Install the whole plugin (CLI)
npx skillmds add huggingface/huggingface-best
npx skillmds add affaan-m/mle-workflow
npx skillmds add google/agent-platform-model-registry
npx skillmds add antigravity/ml-engineer
npx skillmds add majiayu000/awq-quantization
npx skillmds add majiayu000/sft
npx skillmds add sakamoto-family-smile/mle-workflow
npx skillmds add neuralblitz/mlflow
npx skillmds add neuralblitz/tensorflow
npx skillmds add mhassan0000/mle-workflowSkills in this plugin
- ▌ huggingface-best · huggingfaceQueries Hugging Face benchmark leaderboards to find the best AI models for a task, filters by device constraints, and returns a ranked comparison table with scores.
- ▌ mle-workflow · affaan-mTurn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.
- ▌ agent-platform-model-registry · googleManage machine learning models in the Agent Platform Model Registry: list, describe, upload, update, and delete models and their versions.
- ▌ ml-engineer · antigravityBuild production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.
- ▌ awq-quantization · majiayu000 bundleQuantize large language models to 4-bit precision using activation-aware weight quantization, reducing memory footprint and speeding up inference with minimal accuracy loss.
- ▌ sft · majiayu000 bundleFine-tune instruction-following LLMs with Unsloth's optimized SFTTrainer, covering dataset formatting, chat templates, training configuration, and thinking-model patterns.
- ▌ mle-workflow · sakamoto-family-smileTurn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.
- ▌ mlflow · neuralblitzManages the machine learning lifecycle with experiment tracking, model versioning, reproducible runs, and deployment through the MLflow platform.
- ▌ tensorflow · neuralblitzBuild and deploy machine learning models with TensorFlow, covering Keras, data pipelines, and production serving.
- ▌ mle-workflow · mhassan0000Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.