run2_simpo-loss
From the author
Complete implementation of the SimPO (NeurIPS 2024) loss function with all variants and edge cases - use when reproducing SimPO or implementing reference-free preference optimization.
Install
npx skills add cxcscmu/SkillLearnBench --skill run2_simpo-loss -a claude-code
Installs to .claude/skills/run2_simpo-loss/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Why 83
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Similar skills
Closest to this one by what they do and when they are used.
- simpo-losscxcscmu/SkillLearnBenchImplement the SimPO (Simple Preference Optimization) loss function from the NeurIPS 2024 paper. Use this skill whenever implementing SimPO, preference optimization losses, or DPO variants that use length-normalized rewards and reward margins.Science★ 91
- simpo-loss-functioncxcscmu/SkillLearnBenchImplement SimPO loss with length-normalized rewards and target margin.Other★ 91
- evo-simpo-code-reproductionOpenLAIR/OpenSkillImplements the SimPO (Simple Preference Optimization) loss function and handles environment setup, execution, and result saving for code reproduction tasks.Engineering★ 97
- simpo-trainingKalarisLabs/research-agent-skillsSimple 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.Other★ 61
- preference-optimizationwshobson/agentsAlign a fine-tuned model with preference data using DPO, ORPO, KTO, or SimPO. Use when preference pairs or thumbs-up/down feedback exist, when choosing between preference-optimization methods, or when a DPO run needs hyperparameters or debugging.Engineering★ 41.7K
- dspy-simba-optimizerOmidZamani/dspy-skillsUse for SIMBA optimization, mini-batch introspective optimization, self-reflective rules, stochastic ascent, and numeric-metric optimization.Other★ 124
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