Stars
A high-throughput and memory-efficient inference and serving engine for LLMs
Efficient Triton Kernels for LLM Training
A simple code-base for finetuning Large Language Models for classification tasks.
Scripts for fine-tuning Meta Llama with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting…
[ICLR2024] Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
The simplest, fastest repository for training/finetuning medium-sized GPTs.
[KDD 2023] Deep Pipeline Embeddings for AutoML
Multi-modal meta-learning for time series regression
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
[NeurIPS 2022] Supervising the Multi-Fidelity Race of Hyperparameter Configurations
[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.
[ICLR 2023] Deep Ranking Ensembles for Hyperparameter Optimization
This is the official implementation of TrivialAugment and a mini-library for the application of multiple image augmentation strategies including RandAugment and TrivialAugment.
[ICLR 2021] Few Shot Bayesian Optimization
[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
Acceptance rates for the major AI conferences
A learning curve benchmark on OpenML data
[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
Go database seeder inspired from Laravel/Lumen seeder and more
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search https://arxiv.org/abs/1807.06906