QLoRA | BestHub

58 Tech

Jun 3, 2024 · Artificial Intelligence

Parameter-Efficient Fine-Tuning (PEFT) Methods for Large Language Models: LoRA, QLoRA, AdaLoRA, SoRA, and Training Acceleration with Unsloth

This article systematically analyzes popular parameter‑efficient fine‑tuning (PEFT) techniques for large language models—including Adapter Tuning, Prefix Tuning, LoRA, QLoRA, AdaLoRA, and SoRA—detailing their principles, implementation code, experimental results on NLU tasks, and practical acceleration using the Unsloth library.

AdaLoRALoRAPEFT

0 likes · 39 min read

Parameter-Efficient Fine-Tuning (PEFT) Methods for Large Language Models: LoRA, QLoRA, AdaLoRA, SoRA, and Training Acceleration with Unsloth

OPPO Kernel Craftsman

Mar 22, 2024 · Artificial Intelligence

InternLM Model Fine-Tuning Tutorial with XTuner: Chat Format and Practical Implementation Guide

This tutorial walks through fine‑tuning Shanghai AI Lab’s open‑source InternLM models with XTuner, explaining chat‑format conventions, loading and inference (including multimodal InternLM‑XComposer), dataset preparation, configuration sections, DeepSpeed acceleration, and memory‑efficient QLoRA details for 7‑B‑parameter chat models.

Chat FormatDeepSpeedFine-tuning

0 likes · 22 min read

InternLM Model Fine-Tuning Tutorial with XTuner: Chat Format and Practical Implementation Guide

Rare Earth Juejin Tech Community

Jan 21, 2024 · Artificial Intelligence

Understanding Pretraining and Fine‑Tuning of Large Language Models: Methods, Resources, and Practical Applications

This article explains the concepts of pretraining and fine‑tuning for large language models, compares full‑parameter, LoRA and QLoRA approaches, discusses resource consumption, introduces the ModelScope SWIFT framework with code examples, and shows how fine‑tuning can improve data‑visualisation tasks while reducing token usage.

Data VisualizationFine-tuningLLM

0 likes · 24 min read

Understanding Pretraining and Fine‑Tuning of Large Language Models: Methods, Resources, and Practical Applications

DeWu Technology

Jul 5, 2023 · Artificial Intelligence

Fine-tuning Large Language Models with LoRA/QLoRA and Deploying via GPTQ Quantization on KubeAI

The article explains how LoRA and its 4‑bit QLoRA extension dramatically reduce trainable parameters and GPU memory for fine‑tuning large language models, while GPTQ post‑training quantization compresses weights for cheap inference, and shows how KubeAI integrates these techniques into a one‑click workflow for 7 B, 13 B, and 33 B models from data upload to API deployment.

GPTQKubeAILoRA

0 likes · 13 min read

Fine-tuning Large Language Models with LoRA/QLoRA and Deploying via GPTQ Quantization on KubeAI