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neerajcodz/ml-stack

v0.2.0MIT

Requirements-driven ML research, experiments, validation, and evidence audit for coding agents.

ml-stack-training

Design advanced ML training when a user asks for SFT, DPO, GRPO, reward modeling, LoRA, QLoRA, sentence-transformer, vision, checkpointing, Trackio, or HF persistence; emit an executable specification unless an equivalent runtime operation exists.

Read SKILL.md at the source

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