Master Thesis on "Comparing Modular Approaches for Parameter-Efficient Fine-Tuning"
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Updated
Jan 7, 2024 - Python
Master Thesis on "Comparing Modular Approaches for Parameter-Efficient Fine-Tuning"
Applied Deep Learning 深度學習之應用 by Vivian Chen 陳縕儂 at NTU CSIE
Low Tensor Rank adaptation of large language models
PANDA: Prompt Transfer Meets Knowledge Distillation for Efficient Model Adaptation
Official implementation of CVPR 2024 paper "Prompt Learning via Meta-Regularization".
Code for fine-tuning Llama2 LLM with custom text dataset to produce film character styled responses
Evaluate robustness of adaptation methods on large vision-language models
The code for generating natural distribution shifts on image and text datasets.
This project is an implementation of the paper: Parameter-Efficient Transfer Learning for NLP, Houlsby [Google], ICML 2019.
The code for the paper "Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models" (ICCV'23).
Code for SAFT: Self-Attention Factor-Tuning, a 16x more efficient solution for fine-tuning neural networks
[CVPR2024] The code of "UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory"
Code for the Findings of NAACL 2022(Long Paper): AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks
Code for EACL'23 paper "Udapter: Efficient Domain Adaptation Using Adapters"
[NeurIPS-2022] Annual Conference on Neural Information Processing Systems
Multi-domain Recommendation with Adapter Tuning
[ICRA 2024] Official Implementation of the Paper "Parameter-efficient Prompt Learning for 3D Point Cloud Understanding"
This repository contains the source code for the paper "Grouped Pointwise Convolutions Reduce Parameters in Convolutional Neural Networks".
This is AlpaGasus2-QLoRA based on LLaMA2 with AlpaGasus mechanism using QLoRA!
[MICCAI ISIC Workshop 2023] AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets (an official implementation)
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