#lora-adapter

Document Image to Markdown Generation using Qwen2-VL and QLoRA

Introduction

Deploying a LoRA-Fine-Tuned Model on a Quantized Base Model

Fine-Tuning for Ollama: A Practical Tutorial (Prereqs → Deploy)

Prerequisites & expected outcomes

How to Use Hugging Face Multi-LoRA Adapters

In the previous article, we explored the mechanics behind LoRA (Low-Rank Adaptation) and its growing importance in adapting large-scale…

Building Dynamic Multi-Expert AI: Switching Between Specialized LoRA Adapters in Real-Time, Part 1

LoRA (Low-Rank Adaptation) is a breakthrough technique for fine-tuning large models efficiently by adding low-rank matrices to existing…

Model Context Protocol (MCP) vs. LoRA Adapter Training: A Paradigm Shift in Model Customization

Introduction

RAG vs. Fine-Tuning: When to Retrieve and When to Train

LLMs are quickly becoming a core part of modern tooling — but choosing how to adapt them to your use case isn’t always obvious. Two of the…

Demystifying LoRA: Enhancing Large Language Models with Low-Rank Adaptation

Hello reader, In this article I will help you to understand with particle examples on the LoRA (Low-Rank Adaptation) for fine-tune the…

Use Unsloth LORA Adapter with Ollama in 3 Steps

Use LLama.Cpp to convert Unsloth Lora Adapter to GGML(.bin) and use it in Ollama — with a single GPU

Experiment with LLM Model Merging Techniques

In this article, I will share my views on the innovative method of model blending techniques and algorithms, and discuss the results of my…