PEFT
  • 🌍GET STARTED
    • BOINC AI PEFT
    • Quicktour
    • Installation
  • 🌍TASK GUIDES
    • Image classification using LoRA
    • Prefix tuning for conditional generation
    • Prompt tuning for causal language modeling
    • Semantic segmentation using LoRA
    • P-tuning for sequence classification
    • Dreambooth fine-tuning with LoRA
    • LoRA for token classification
    • int8 training for automatic speech recognition
    • Semantic similarity with LoRA
  • 🌍DEVELOPER GUIDES
    • Working with custom models
    • PEFT low level API
    • Contributing to PEFT
    • Troubleshooting
  • 🌍ACCELERATE INTEGRATIONS
    • DeepSpeed
    • PagFully Sharded Data Parallele 2
  • 🌍CONCEPTUAL GUIDES
    • LoRA
    • Prompting
    • IA3
  • 🌍REFERENCE
    • PEFT model
    • Configuration
    • Tuners
Powered by GitBook
On this page
  • Installation
  • PyPI
  • Source
  1. GET STARTED

Installation

Installation

Before you start, you will need to setup your environment, install the appropriate packages, and configure 🌍 PEFT. 🌍 PEFT is tested on Python 3.8+.

🌍 PEFT is available on PyPI, as well as GitHub:

PyPI

To install 🌍 PEFT from PyPI:

Copied

pip install peft

Source

New features that haven’t been released yet are added every day, which also means there may be some bugs. To try them out, install from the GitHub repository:

Copied

pip install git+https://github.com/boincai/peft

If you’re working on contributing to the library or wish to play with the source code and see live results as you run the code, an editable version can be installed from a locally-cloned version of the repository:

Copied

git clone https://github.com/boincai/peft
cd peft
pip install -e .
PreviousQuicktourNextTASK GUIDES

Last updated 1 year ago

🌍