melisilaydabal's Stars
mlabonne/llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
karpathy/LLM101n
LLM101n: Let's build a Storyteller
tpn/pdfs
Technically-oriented PDF Collection (Papers, Specs, Decks, Manuals, etc)
dair-ai/ML-Course-Notes
🎓 Sharing machine learning course / lecture notes.
togethercomputer/RedPajama-Data
The RedPajama-Data repository contains code for preparing large datasets for training large language models.
llm-attacks/llm-attacks
Universal and Transferable Attacks on Aligned Language Models
facebookresearch/esm
Evolutionary Scale Modeling (esm): Pretrained language models for proteins
QData/TextAttack
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
paperswithcode/releasing-research-code
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
mlabonne/llm-datasets
High-quality datasets, tools, and concepts for LLM fine-tuning.
thunlp/TAADpapers
Must-read Papers on Textual Adversarial Attack and Defense
Peldom/papers_for_protein_design_using_DL
List of papers about Proteins Design using Deep Learning
epfml/OptML_course
EPFL Course - Optimization for Machine Learning - CS-439
MadryLab/robustness
A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.
bayesoptbook/bayesoptbook.github.io
Companion webpage for the book "Bayesian Optimization" by Roman Garnett
weijiaheng/Advances-in-Label-Noise-Learning
A curated (most recent) list of resources for Learning with Noisy Labels
jxzhangjhu/Awesome-LLM-Uncertainty-Reliability-Robustness
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
vwxyzjn/ppo-implementation-details
The source code for the blog post The 37 Implementation Details of Proximal Policy Optimization
songhwanjun/Awesome-Noisy-Labels
A Survey
chinasatokolo/csGraduateFellowships
A curated list of fellowships for graduate students in Computer Science and related fields.
sacdallago/bio_embeddings
Get protein embeddings from protein sequences
peggy1502/Amazing-Resources
List of references and online resources related to data science, machine learning and deep learning.
SheffieldML/notebook
Collection of jupyter notebooks for demonstrating software.
jeromerony/adversarial-library
Library containing PyTorch implementations of various adversarial attacks and resources
i-gallegos/Fair-LLM-Benchmark
weijiaheng/Robust-f-divergence-measures
[ICLR2021] Official Pytorch implementation of "When Optimizing f-Divergence is Robust with Label noise"
facebookresearch/bo_pr
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
chrodan/tdlearn
some common TD Learning algorithms
clementapa/CelebFaces_Attributes_Classification
This repository is related to a project of the Introduction to Numerical Imaging (i.e, Introduction à l'Imagerie Numérique in French), given by the MVA Masters program at ENS-Paris Saclay. It was entirely build from scratch and contains code in PyTorch Lightning to train and then use a neural network for image classification. We used it to create a classifier allowing semantic attributes classification of faces with the dataset CelebA-HQ.
zixu1986/Doubly_Stochastic_Gradients
Code for doubly stochastic gradients