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What is Fine-Tuning? Fine-tuning is the process of taking a pre-trained model (like GPT, BERT, LLaMA, etc.) and continuing its training on a smaller, task-specific dataset. The goal is to adapt the model's general knowledge to perform better on a par...

La generación de avatares y personajes únicos con IA está revolucionando múltiples industrias, desde el entretenimiento hasta el marketing digital. En este artículo, exploramos cómo esta tecnología permite crear personajes altamente personalizables u...

1. Introduction Retrieval-Augmented Generation (RAG) models combine retrieval and generation techniques to improve the accuracy and relevance of generated responses in question-answering contexts. By leveraging both retrieval and generation, RAG mode...

I've been trying my hand at Transfer Learning and Fine Tuning for a while now. I decided to utilise it for a fun little project around F1. I fine-tuned the EfficientNetB0 image classification model on a F1 car images dataset, so that, given an image ...

In this post, I will outline the steps I followed to fine-tune a model using Axolotl and Jarvislabs.ai. This post is based on https://maven.com/parlance-labs/fine-tuning and https://medium.com/@andresckamilo/finetuning-llms-using-axolotl-and-jarvis-a...

Introduction Ever felt like taming a giant language model is a bit like wrestling an octopus? Large Language Models (LLMs) represent a breakthrough in AI, but their training can be resource-intensive. Enter LoRA (Low-Rank Adaptation) - your secret sa...
