simpo-training

Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.

[Post-TrainingSimPOPreferenceOptimization

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axolotl

Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).

[Fine-TuningAxolotlLLMLoRA

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obliteratus

OBLITERATUS: abliterate LLM refusals (diff-in-means).

[AbliterationUncensoringRefusal-RemovalLLM

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nemo-curator

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

[DataProcessingNeMoCurator

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