Leaderboard/Automation/unsloth-buddy
Last commit on May 6, 2026·Created on March 15, 2026

TYH-labs/unsloth-buddy

Fits bigger models onto smaller GPUs without losing accuracy.
Combined rank
#368
across all skills
In Automation
#26
category rank
Stars
270
+0.4% in last 7d
Forks
14
+7.7% in last 7d
Watchers
1
0.0% in last 7d
Traction scoreGitHub stars can be faked, so popularity alone can be misleading. Traction Score looks for broader signs of real attention, adoption, and active maintenance.
Description

This skill guides fine-tuning and reinforcement learning for large language models using the Unsloth library, which cuts VRAM usage by up to 80% with zero accuracy loss. It helps ML engineers and AI researchers training on limited hardware—consumer GPUs, Apple Silicon Macs, or free Colab T4s—by handling environment setup, LoRA patching, data formatting, and deployment export to GGUF, Ollama, or vLLM. The assistant follows a structured 7-phase lifecycle from project initialization through evaluation, demo generation, and memory reflection.

WHO IT'S FOR
ML Engineers Fine-Tuning LLMs
fine-tune language models with limited VRAM
Apple Silicon ML Practitioners
train models on Mac using mlx-tune
AI Researchers Doing RL Fine-Tuning
apply reinforcement learning to align models
Developers Deploying Fine-Tuned Models
export and deploy models to production
30 Days of GitHub Stars
+12 stars
↑ 4.7% monthly change
Jul 7Jul 14Jul 21Jul 28Aug 5
Compatibility & Install
1 Skill · 5 Compatible agents · 3 categories · 1 install path
Compatible agents
Claude CodeCodexGemini CLIOpenClawDeepSeek
Categories
AutomationSoftware EngineeringDeveloper Tooling
Install via
Other documented method
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