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NUS CS5242 Neural Networks and Deep Learning, Xavier Bresson, 2025
Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷
Pytorch implementation of DoReMi, a method for optimizing the data mixture weights in language modeling datasets
Must-read papers on prompt-based tuning for pre-trained language models.
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
A curated list of resources for Learning with Noisy Labels
A collection of libraries to optimise AI model performances
Implementation of papers in 100 lines of code.
Materials for the Hugging Face Diffusion Models Course
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Cramming the training of a (BERT-type) language model into limited compute.
🚀 Level up your GitHub profile readme with customizable cards including LOC statistics!
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
A curated list of awesome self-supervised methods
A collection of papers on the topic of ``Computer Vision in the Wild (CVinW)''
This repository contains demos I made with the Transformers library by HuggingFace.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。
A curated list of neural network pruning resources.
Tips for Writing a Research Paper using LaTeX
COCO Synth provides tools for creating synthetic COCO datasets.
CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning
A Python library to capture the energy consumption of code snippets