mode LLM Training
peft-expert-mode
HuggingFace PEFT library survey — LoRA, IA3, prompt tuning, prefix tuning, AdaLoRA, OFT/BOFT, VeRA
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axolotl-expert-mode
Axolotl — YAML-driven LLM fine-tuning with LoRA/QLoRA, DPO/GRPO, DeepSpeed, FSDP
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Teacher-student LLM distillation — logits, on-policy distillation, context distillation
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Weight-Decomposed Low-Rank Adaptation — magnitude + direction split for better LoRA quality
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Direct Preference Optimization — preference alignment without an explicit reward model
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Evaluate fine-tuned LLMs — domain benchmarks, regression checks, catastrophic forgetting detection
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Group Relative Policy Optimization — DeepSeek-R1 style reasoning RL with verifiable rewards
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