mode LLM Training
orpo-expert-mode
Odds-Ratio Preference Optimization — single-stage SFT + preference alignment without a reference model
More in LLM Training
mode
axolotl-expert-mode
Axolotl — YAML-driven LLM fine-tuning with LoRA/QLoRA, DPO/GRPO, DeepSpeed, FSDP
View → modedistillation-expert-mode
Teacher-student LLM distillation — logits, on-policy distillation, context distillation
View → modedora-expert-mode
Weight-Decomposed Low-Rank Adaptation — magnitude + direction split for better LoRA quality
View → modedpo-expert-mode
Direct Preference Optimization — preference alignment without an explicit reward model
View → modefine-tune-eval-expert-mode
Evaluate fine-tuned LLMs — domain benchmarks, regression checks, catastrophic forgetting detection
View → modegrpo-expert-mode
Group Relative Policy Optimization — DeepSeek-R1 style reasoning RL with verifiable rewards
View →