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unsloth-training

Fine-tune LLMs with Unsloth kernels supporting SFT, DPO, GRPO, and GGUF export.

17|3|Updated Apr 3, 2026
Search Tags:#llm#quantization#vllm#finetuning#gguf#trl#unsloth
One-click install
npx skills add https://github.com/jayll1303/AIEKit --skill unsloth-training-jayll1303
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: unsloth-training
Source: https://github.com/jayll1303/AIEKit/tree/main/.kiro/skills/unsloth-training
Command: npx skills add https://github.com/jayll1303/AIEKit --skill unsloth-training-jayll1303

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Fine-tune large language models efficiently by significantly reducing VRAM usage and accelerating training with Unsloth's optimized kernels and 4-bit quantization.

Core Features & Use Cases

  • Supports supervised fine-tuning (SFT), preference optimization (DPO), and policy optimization (GRPO) workflows using TRL trainers.
  • Includes model export options (GGUF, merged) and prep paths for vLLM serving or Ollama integration.
  • Provides a practical end-to-end pipeline from dataset preparation to export and serving readiness.

Quick Start

Prepare your dataset and run the Unsloth fine-tuning workflow with TRL trainers on a pre-quantized model.

Frequently Asked Questions about unsloth-training

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

FAQPage Schema
How do I fine-tune an LLM with less VRAM using Unsloth?▼

Fine-tune large language models with less VRAM by using Unsloth's Triton-accelerated kernels and 4-bit quantization, which reduces memory usage by ~70% and accelerates training by up to 2x.

Does Unsloth support DPO and GRPO training workflows?▼

Yes, Unsloth supports supervised fine-tuning (SFT), direct preference optimization (DPO), and generative reward policy optimization (GRPO) workflows using TRL-based trainers.

What's the best way to export a fine-tuned model to GGUF for Ollama?▼

Export fine-tuned models to GGUF or merged formats and prepare them directly for vLLM serving or Ollama integration as part of the end-to-end pipeline.

Can I use Unsloth with pre-quantized 4-bit bnb models?▼

Yes, you can use Unsloth with compatible pre-quantized models, such as 4-bit bitsandbytes (bnb) variants, to maximize VRAM savings during training.

Are there limitations to accelerating LLM training with Unsloth?▼

Unsloth requires installing its specific packages, accessing TRL-based trainers and datasets, and using compatible pre-quantized models to achieve its 2x training speedup and 70% VRAM reduction.

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