Results for “simpo”
14 skills
orchestra-research Simpo Training
Train language models with SimPO, a reference-free preference optimization method that outperforms DPO without needing a reference model.
10.4k · bundle
lord1egypt Simpo Training
Trains LLMs with SimPO, a reference-free preference optimization method that outperforms DPO, using configurable hyperparameters and workflows for various models and tasks.
2
tianhao909 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.
1 · bundle
More results
qcmuu 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.
0 · bundle
aniruddhaadak80 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.
0 · bundle
peteedoo 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.
0 · bundle
schattenspiegel Simpy Python
Use for writing, reviewing, debugging, testing, or analyzing Python SimPy discrete-event simulations. Trigger on Environment, Event, Process, timeout, Resource, PriorityResource, PreemptiveResource, Container, Store, queues, interrupts, simulation clocks, replications, or SimPy monitoring. Do not use for asyncio services, wall-clock schedulers, continuous ODE solvers, or Monte Carlo code without an event-process model.
0 · bundle
nimoqup046-collab Sympy
Provides comprehensive guidance for performing symbolic mathematics with SymPy, including algebra, calculus, equation solving, linear algebra, physics calculations, and code generation.
2
lingxling Sympy
Provides guidance for using SymPy for exact symbolic mathematics in Python, covering algebra, calculus, equation solving, linear algebra, physics, and code generation.
253 · bundle
lucaspmarie-a11y Sympy
Provides comprehensive guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using the SymPy Python library.
5
phoroth Sympy
Provides guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using the SymPy Python library.
3
lingxling Pymoo
Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.
253 · bundle
jorcan Sympy
Provides comprehensive guidance for symbolic mathematics in Python using SymPy, covering algebra, calculus, equation solving, linear algebra, physics, and code generation.
0 · bundle
akillness Soup
Drive Soup (`soup-cli`), a CLI-first tool for fine-tuning and post-training LLMs with one YAML config and one command — SFT, DPO/GRPO/ORPO/SimPO/KTO, QLoRA/DoRA/LoRA+, layer streaming for 4-8 GB GPUs, eval-gated training, and serving. Use when the user wants to `soup init`/`soup train` a model, pick a training method or quantization scheme, estimate cost/memory before training, fine-tune on a small local GPU, migrate a config from Axolotl/LLaMA-Factory/Unsloth, or serve/merge/push a trained adapter. Triggers on: "soup-cli", "soup train", "soup init", "fine-tune an LLM locally", "QLoRA on a laptop GPU", "layer streaming", "soup advise", "soup autopilot", "DPO/GRPO/ORPO training", "merge LoRA adapter".
42 · bundle