llm-fine-tuning
CommunityFine-tune LLMs with modern techniques at scale.
Authorpunkt2
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Fine-tune large language models efficiently using modern techniques (QLoRA, Spectrum, full fine-tuning) with TRL and PEFT, enabling domain adaptation and customization for specific tasks.
Core Features & Use Cases
- Supports QLoRA on consumer GPUs with 4-bit quantization and LoRA adapters.
- Provides Spectrum and full fine-tuning workflows with distributed training support (DeepSpeed ZeRO3, FSDP) and model merging.
- Covers dataset preparation, training configuration, evaluation, and post-training steps including merging adapters and pushing to hub.
Quick Start
Run the supervised fine-tuning workflow by executing the training script with a YAML config.
Dependency Matrix
Required Modules
torchtransformerstrlpeftdatasetshuggingface_hubliger_kernel
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: llm-fine-tuning Download link: https://github.com/punkt2/llm-fine-tuning-skill/archive/main.zip#llm-fine-tuning Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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