# Beyond LoRA: Can you beat the most popular fine-tuning technique?

DevFeed: [Beyond LoRA: Can you beat the most popular fine-tuning technique?](<https://devfeed.tech/articles/beyond-lora-can-you-beat-the-most-popular-fine-tuning-technique-7439.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/peft-beyond-lora>)

Author: Benjamin Bossan; Sayak Paul; Marian Tietz; Kashif Rasul

Published: 2026-06-18T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>), [SDKs](<https://devfeed.tech/topics/sdks.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [community](<https://devfeed.tech/tags/community.md>), [diffusers](<https://devfeed.tech/tags/diffusers.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [guide](<https://devfeed.tech/tags/guide.md>), [lora](<https://devfeed.tech/tags/lora.md>), [nlp](<https://devfeed.tech/tags/nlp.md>), [peft](<https://devfeed.tech/tags/peft.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [stable-diffusion](<https://devfeed.tech/tags/stable-diffusion.md>), [training](<https://devfeed.tech/tags/training.md>), [transformers](<https://devfeed.tech/tags/transformers.md>)

## AI overview

The article examines parameter-efficient fine-tuning (PEFT) for open models, focusing on whether LoRA is always the best technique. It explains how PEFT reduces memory requirements, can enable fine-tuning of quantized models, and offers a unified API for multiple techniques.

## Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.