Fine-tuning - TechnoScripts

fine-tuning

Guides on fine-tuning pretrained machine learning models on your own data with Python.

NLP: Text Classification with HuggingFace Transformers

A real text classifier in under 50 lines of code is a realistic goal with the Python HuggingFace stack. The Transformers library is the go-to toolkit for modern Natural Language Processing (NLP), and this post uses it end to end: you load a pre-trained model, turn text into tokens, fine-tune on your own labeled data, and run a working sentiment analysis pipeline. “The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge.” Daniel J. Boorstin Last ... Read More

GenAI: Introduction to Large Language Models

A few years ago, the idea that large language models could write a passable email felt like science fiction. Today they write production code, reason through tricky math, and hold conversations that fool experienced engineers. The strangest part: nobody programmed those abilities in. They appeared once models crossed a size threshold, and this guide maps how that happened and what it means for your projects. You already understand Transformers and attention, plus BERT vs GPT, from the earlier lessons. Now ... Read More

DL: Transfer Learning with ResNet, VGG Pre-trained Models

Transfer learning lets you reuse a model that already learned to see, then point it at your own problem with a tiny dataset. This transfer learning Python guide shows feature extraction versus fine-tuning with ResNet, VGG, and EfficientNet, so you can classify custom images with far less data than training a network from scratch. “After supervised learning, transfer learning will be the next driver of ML commercial success.” Andrew Ng, NIPS 2016 tutorial Last Updated: July 2026 | Tested on: ... Read More