stas00/ml-engineering
ml-engineering
Machine Learning Engineering Open Book
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stas00
stas00 • individual
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Created
Sep 2, 2020
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README Summary
This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.
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Data Pipeline EngineeringDistributed TrainingExperiment TrackingMachine Learning Operations (MLOps)Model DeploymentModel Serving ArchitectureModel Training and OptimizationModel VersioningPerformance MonitoringProduction ML SystemsResource ManagementTraining Infrastructure
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Data Pipeline EngineeringDistributed TrainingExperiment TrackingMachine Learning Operations (MLOps)Model DeploymentModel Serving ArchitectureModel Training and OptimizationModel VersioningPerformance MonitoringProduction ML SystemsResource ManagementTraining InfrastructureBenchmarkingCheat SheetCourseCurated ListData ScienceEvalsForkedHuggingFaceLarge Language ModelsMachine LearningPyTorchPython
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category
Deployment Context
Modalities
Skill Areas
tag
Recent Activity
Updated 2 months ago
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90 Days
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Quality
production- Quality
- high
- Maturity
- production
Categories
Learning ResourcesPrimaryEvals & BenchmarkingData Science & AnalyticsFoundation ModelsModel TrainingOther AI / ML
PM Skills
Data & Evaluation
Languages
Python100.0%
Timeline
- Project created
- Sep 2, 2020
- Forked
- Mar 23, 2026
- Your last push
- 2 months ago
- Upstream last push
- 16 days ago
- Tracked since
- Mar 16, 2026
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