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image-gen21,781Apache 2.0

peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Updated Oct 12, 2026
Website GitHub Docs
Platforms
Pricing
free-open-source
Status
active
License
Apache 2.0

What it does

Core capabilities at a glance

  • Adapter
  • Diffusion
  • Fine Tuning
  • Lora
  • Parameter Efficient Learning
  • Peft
  • Pytorch
  • Transformers

Deep dive

The full breakdown - performance, comparisons, and setup

peft

peft is an image-generation tool - 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Overview

Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters. This significantly decreases the computational and storage costs. Recent state-of-the-art PEFT techniques achieve performance comparable to fully fine-tuned models.

PEFT is integrated with Transformers for easy model training and inference, Diffusers for conveniently managing different adapters, and Accelerate for distributed training and inference for really big models.

Check the PEFT Adapters API Reference section for a list of supported PEFT methods, and read the Adapters, Soft prompts, and IA3 conceptual guides to learn more about how these methods work.

Prepare a model for training with a PEFT method such as LoRA by wrapping the base model and PEFT configuration with 'get_peft_model'. For the bigscience/mt0-large model, you're only training 0.19% of the parameters!

There are many benefits of using PEFT but the main one is the huge savings in compute and storage, making PEFT applicable to many different use cases.

Consider the memory requirements for training the following models on the ought/raft/twitter_complaints dataset with an A100 80GB GPU with more than 64GB of CPU RAM.

peft is open-source, written primarily in Python, with 21,781 GitHub stars under the Apache 2.0 license. The latest release is v0.21.2 (2026-10-01).

Install

A quick way to get started (always check the official docs for the latest):

pip install peft

How it fits a local-AI stack

peft runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related image-generation tools in the directory:

Sources

Stats from GitHub, 2026-10-12.

Frequently asked

Quick answers to common questions

What is peft?

peft is a image-gen tool for local AI workloads. 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Is peft free and open source?

Yes, peft has 21,781 GitHub stars and is licensed under Apache 2.0. You can self-host it for free on .

What hardware do I need for peft?

The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. peft has 21,781 GitHub stars and an active community.

Does peft support GPU acceleration?

peft's GPU support depends on your specific setup. Check the documentation for details. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.

What are the best alternatives to peft?

Popular alternatives include other image-gen tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.

How much does peft cost?

peft is free-open-source. It is completely free and open source to self-host.

Pairs well with

Complementary tools, models, and hardware