finetuning
CommunityFine-tune LLMs efficiently with PyTorch & HF.
Authoratrawog
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Fine-tune domain-specific LLMs to adapt generic models to specific tasks and data distributions, improving performance on targeted use cases.
Core Features & Use Cases
- End-to-end fine-tuning with PyTorch and HuggingFace Trainer (HF Trainer) including dataset prep, tokenization, TrainingArguments, and SFTTrainer.
- Supports Unsloth-optimized workflows for faster training and efficient resources.
- Use Case: fine-tuning a base LLM on customer support data to improve instruction-following in FAQs.
Quick Start
Fine-tune a model on a task-specific dataset using Unsloth-enabled SFTTrainer.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 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: finetuning Download link: https://github.com/atrawog/overthink-plugins/archive/main.zip#finetuning Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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