Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"
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Updated
Mar 10, 2024 - Python
Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"
Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
PyTorch code for "VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks" (CVPR2022)
Collection of Tools and Papers related to Adapters / Parameter-Efficient Transfer Learning/ Fine-Tuning
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021
Code of NAACL 2022 "Efficient Hierarchical Domain Adaptation for Pretrained Language Models" paper.
This repositary hosts my experiments for the project, I did with OffNote Labs.
Code for EACL'23 paper "Udapter: Efficient Domain Adaptation Using Adapters"
Systems submitted to IWSLT 2022 by the MT-UPC group.
A TensorFlow 2.0 implementation of Adapters in NLP based on HuggingFace's Transformers.
Master Thesis on "Comparing Modular Approaches for Parameter-Efficient Fine-Tuning"
Ready-to-run training scripts for Transformers and Adapters on >50 NLP tasks
Sequencing adapters and contaminants collected from different tools for easy download
Official implementation and data for our ICPC '22 paper "On The Cross-Modal Transfer from Natural Language to Code through Adapter Modules"
Python samples for Reports.PYTHON report builder for Python 3.10 and higher, and embedded report designer and report viewer
This project is an implementation of the paper: Parameter-Efficient Transfer Learning for NLP, Houlsby [Google], ICML 2019.
Contains the implementation for my master's thesis, titled: "Tackling distribution shifts in multilabel text classification using Adapters"
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