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Training

Skills/MLOps
MLOps

Training

Guides fine-tuning and post-training work with explicit data, objective, hardware, and rollback assumptions.

On demandAvailable when invokedBuilt In
Install from Aegisaegis skills install training
Install guide
Overview

Bundled with the packaged Aegis CLI as a built-in procedural skill.

Already ships inside the packaged Aegis bundle. Use `aegis skills install training` only when you want an explicit local materialization record.

Aliases

model trainingfine tuningpost training

Trigger phrases

fine tune this modelplan a training runset up post-training for this model

Keywords

trainingfine-tuningpost-trainingdataobjectivecheckpoint
Same section

More from MLOps

5 skills in this section

Evaluation

Frames model, prompt, and system evaluation as a reproducible experiment with baselines, datasets, and explicit metrics.

On demandAvailable when invoked
Usage and install
Slash command
/evaluation
Install
aegis skills install evaluation
Reference
evaluation
Runtime posture
Available when invoked
Open details
Hugging Face Hub

Guides model, dataset, and space workflows around Hugging Face Hub with explicit auth, artifact, and cache assumptions.

On demandAvailable when invoked
Usage and install
Slash command
/huggingface-hub
Install
aegis skills install huggingface-hub
Reference
huggingface-hub
Runtime posture
Available when invoked
Open details
Inference

Guides model-serving and runtime-inference decisions across local, remote, and packaged deployment paths.

On demandAvailable when invoked
Usage and install
Slash command
/inference
Install
aegis skills install inference
Reference
inference
Runtime posture
Available when invoked
Open details