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

A Unified Library for Parameter-Efficient and Modular Transfer Learning

An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks

A plug-and-play library for parameter-efficient-tuning (Delta Tuning)

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

Live Training for Open-source Big Models

A collection of parameter-efficient transfer learning papers focusing on computer vision and multimodal domains.

Research Trends in LLM-guided Multimodal Learning.

Collection of Tools and Papers related to Adapters / Parameter-Efficient Transfer Learning/ Fine-Tuning

[Pattern Recognition 2025] Cross-Modal Adapter for Vision-Language Retrieval

K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of examples and documentation.

CodeUp: A Multilingual Code Generation Llama-X Model with Parameter-Efficient Instruction-Tuning

This Repository surveys the paper focusing on Prompting and Adapters for Speech Processing.

On Transferability of Prompt Tuning for Natural Language Processing

[CVPR2024] The code of "UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory"

INTERSPEECH 23 - Refunction Whisper to recognize new tasks with adapters!

Code for the ACL 2022 paper "Continual Sequence Generation with Adaptive Compositional Modules"

[EMNLP'25 main] Official Implementation of ModalPrompt: Towards Efficient Multimodal Continual Instruction Tuning with Dual-Modality Guided Prompt

Code for EACL'23 paper "Udapter: Efficient Domain Adaptation Using Adapters"

[ECCV2024] The code of "SHERL: Synthesizing High Accuracy and Efficient Memory for Resource-Limited Transfer Learning"