# Hugging Face — Parameter-Efficient Fine-Tuning using 🤗 PEFT

- Company: Hugging Face (huggingface.co)
- Announced: 2023-02-10
- Category: developer-tool-release
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://huggingface.co/blog/peft
- Record: https://forck.live/items/2098-parameter-efficient-fine-tuning-using-peft
- Subject: Platform
- Models affected: bigscience/T0_3B, OPT-6.7b, bigscience/mt0-large, bigscience/mt0-xxl

Hugging Face introduces the PEFT library for parameter-efficient fine-tuning of billion-scale models on low-resource hardware. It supports methods like LoRA, Prefix Tuning, Prompt Tuning, and P-Tuning, and is integrated with Transformers and Accelerate, enabling fine-tuning on consumer hardware with tiny checkpoints.

## Evidence

Verbatim from https://huggingface.co/blog/peft:

> Today, we are excited to introduce the 🤗 PEFT library, which provides the latest Parameter-Efficient Fine-tuning techniques seamlessly integrated with 🤗 Transformers and 🤗 Accelerate.

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Record: https://forck.live/items/2098-parameter-efficient-fine-tuning-using-peft
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