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"
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.
Frame Flexible Network (CVPR2023)
Official source code for the paper "Tailored Design of Audio-Visual Speech Recognition Models using Branchformers"
How many parameters are needed to get 99% on MNIST? Personal record of 697 parameters.
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