How I use LLMs for structured classification without getting garbage output

📰 Medium · LLM

Learn how to use Large Language Models (LLMs) for structured classification tasks without getting low-quality output, a crucial skill for automating workflows

intermediate Published 15 Jun 2026

Action Steps

Train an LLM on a labeled dataset using a suitable framework
Fine-tune the LLM for the specific classification task
Configure the LLM to output structured data
Test the LLM on a validation set to evaluate its performance
Apply the trained LLM to classify new, unseen data

Who Needs to Know This

Data scientists and machine learning engineers on a team can benefit from this knowledge to improve the accuracy of their classification models, while software engineers can use it to automate tasks such as categorizing GitHub pull requests

Key Insight

💡 Fine-tuning an LLM on a specific task and using a suitable framework can significantly improve the quality of its output

Key Takeaways

Learn how to use Large Language Models (LLMs) for structured classification tasks without getting low-quality output, a crucial skill for automating workflows

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