simpo-training

Optimize language model preferences without a reference model.

4|Updated Apr 19, 2026

Search Tags:#alignment #preferences #simpo #language model #alignment training

Ready to run

npx skills add https://github.com/ragnarokhaa/hermes --skill simpo-training-ragnarokhaa

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: simpo-training
Source: https://github.com/ragnarokhaa/hermes/tree/main/hermes-cerul-tech-news-package/hermes-cerul-tech-news-package/hermes-agent/optional-skills/mlops/simpo
Command: npx skills add https://github.com/ragnarokhaa/hermes --skill simpo-training-ragnarokhaa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires torch, transformers, datasets, trl, accelerate, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill solves the challenge of aligning language models' preferences, simplifying the process and improving performance over traditional methods like DPO.

Core Features & Use Cases

Preference Alignment: Simple preference optimization method, providing an alternative to DPO for LLM alignment.
Performance: Demonstrates better performance on tasks like AlpacaEval 2.0, without the need for a reference model.
Efficiency: Faster training and more resource-efficient compared to DPO and PPO.
Use Case: Use this Skill to train LLMs more effectively for tasks that require alignment with human preferences.

Quick Start

Train the simpo-training model with the Mistral 7B base model by executing the following command:

ACCELERATE_LOG_LEVEL=info accelerate launch \
  --config_file accelerate_configs/deepspeed_zero3.yaml \
  scripts/run_simpo.py \
  training_configs/mistral-7b-base-simpo.yaml

Frequently Asked Questions about simpo-training

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I align language model preferences without a reference model?▼

SimPO is a simple preference optimization method for aligning LLMs without a reference model, offering faster and more resource-efficient training than DPO. It achieves better performance on benchmarks like AlpacaEval 2.0.

What is the best way to train a Mistral 7B base model for preference alignment?▼

The best way to train a Mistral 7B base model for preference alignment is using accelerate and deepspeed zero3 configurations to launch the SimPO training script. This approach optimizes the model efficiently without requiring a separate reference model.

Does SimPO perform better than DPO for language model alignment?▼

SimPO performs better than DPO by demonstrating higher performance on tasks like AlpacaEval 2.0. It achieves this while offering faster training and greater resource efficiency by eliminating the need for a reference model.

Can I use transformers and trl for preference optimization training?▼

Yes, you can use transformers and trl for preference optimization training. This Skill relies on these libraries along with torch, datasets, and accelerate to perform efficient language model alignment without a reference model.

Do I need a reference model for preference optimization in PyTorch?▼

You do not need a reference model for preference optimization when using SimPO. This method is specifically designed to bypass the reference model requirement, resulting in faster training and lower resource consumption in PyTorch.