Reverse Dependencies of Lightning

The following projects have a declared dependency on Lightning:

• achatbot — An open source chat bot for voice (and multimodal) assistants
• adversarial-insight-ml — no summary
• aidsorb — Python package for deep learning on molecular point clouds.
• aihandler — AI Handler: An engine which wraps certain huggingface models
• aihandlerwindows — AI Handler: An engine which wraps certain huggingface models
• ailoganalyzer — AI-Log-Analyzer is an open source toolkit, user friendly, based on deep-learning, for unstructured log anomaly detection.
• airi-test-task — This library contains the code used to run a test job to AIRI.
• albert-toolkit — Python toolkit for Albert Invent
• allin1 — All-In-One Music Structure Analyzer
• alphafold3-pytorch — Alphafold 3 - Pytorch
• alphafold3-pytorch-lightning-hydra — AlphaFold 3 - Pytorch
• amplfi — Accelerated Multi-messenger PE with Likelihood Free Inference
• Angular-Deviation-Diffuser — This is a Transformer-Based diffusion model for Efficient Protein Conformational Ensemble Generation
• anhaltai-commons-pl-hyper — Commons PyTorch Lightning Trainer for Hyperparmater Optimization
• anomalib — anomalib - Anomaly Detection Library
• anyGPT — A general purpose library for training any type of GPT model. Support for gpt-1, gpt-2, and gpt-3 models.
• anypy — A collection of python utilities, without hard dependencies
• AQMLator — A package for auto quantum machine learning-izing your experiments!
• archai — Platform for Neural Architecture Search
• armory-library — TwoSix Armory Adversarial Robustness Evaluation Library
• art-training — ART - Actually Robust Training framework - a framework that teaches good practices when training deep neural networks.
• ASRChild — Package for ASRChild
• autogluon.multimodal — Fast and Accurate ML in 3 Lines of Code
• autogluon.timeseries — Fast and Accurate ML in 3 Lines of Code
• avdeepfake1m — no summary
• backend-central-dev — no summary
• bayesianflow-for-chem — Bayesian flow network framework for Chemistry
• bert-squeeze — Tools for Transformers compression using PyTorch Lightning
• binn — A package to generate and interpret biologically informed neural networks.
• biodem — Dual-extraction method for phenotypic prediction and functional gene mining
• bionemo-core — BioNeMo core interfaces and PyTorch-related code.
• birdset — BirdSet: A multi-task benchmark and data pipeline for deep learning based avian bioacoustics
• birm-nm-foo — Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularization
• bkh-pytorch-utils — A rapid prototyping tool for MONAI & PyTorch Lightning
• Braindecode — Deep learning software to decode EEG, ECG or MEG signals
• brainways — Brainways
• calvera — Package that will offer a small collection of different (Neural) Bandit algorithms with different feedback strategies.
• casanovo — De novo mass spectrometry peptide sequencing with a transformer model
• cascadia — De novo sequencing for DIA mass spectrometry data
• catchMinor — model library for imbalanced-learning & anomaly detection in tabular, time series, graph data
• cca-zoo — Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework
• cellarium-ml — Machine learning library for single-cell data analysis
• celldisect — Cell DISentangled Experts for Covariate counTerfactuals (CellDISECT). Causal generative model designed to disentangle known covariate variations from unknown ones at test time while simultaneously learning to make counterfactual predictions.
• cellseg-models.pytorch — Python library for 2D cell/nuclei instance segmentation models written with PyTorch.
• cesped — Code utilities for the CESPED (Cryo-EM Supervised Pose Estimation Dataset) benchmark
• charmory — Adversarial Robustness Evaluation Library
• chat-time — ChatTime: A Multimodal Time Series Foundation Model
• chemprop — Molecular Property Prediction with Message Passing Neural Networks
• clarena — An open-source machine learning package for continual learning research
• clarinpl-embeddings — no summary
• classifier_trains — A PyTorch-based deep learning classifier training framework.
• contextualized-ml — A statistical machine learning toolbox for estimating models, distributions, and functions with sample-specific parameters.
• cpa-tools — Compositional Perturbation Autoencoder (CPA)
• crescendo — Machine learning made easy
• curator-torch — Library for implementation of message passing neural networks in Pytorch
• CurriculumAgent — CurriculumAgent is a cleanup and improved version of the NeurIPS 2020 Competition Agent by Binbinchen.The agent is build to extract action sets of the Grid2Op Environment and then use rule-based agent to train a Reinforcement Learning agent.
• cyto-dl — Collection of representation learning models, techniques, callbacks, utils, used to create latent variable models of cell shape, morphology and intracellular organization.
• d3nav — D³Nav: Data-Driven Driving Agents for Autonomous Vehicles in Unstructured Traffic
• dataset-format-benchmark — Image dataset format benchmark
• deep-labelprop — Label propagation using deep registration
• deep-time-series — Deep learning library for time series forecasting based on PyTorch.
• deep-training — an easy training architecture
• deepbio-toolkit — A collection of various deep-learning and data handling tools for running and building deep-learning models for computational biology.
• deepchopper — A Genomic Language Model for Chimera Artifact Detection in Nanopore Direct RNA Sequencing
• deepehrgraph — no summary
• deeplay — An AI-powered platform for advancing deep learning research and applications, developed by DeepTrackAI.
• deeptrees — Tree crown segmentation and analysis in remote sensing imagery with PyTorch
• demonstrable-whisperx-service — A standalone service for transcribing audio files using WhisperX
• detoxai — todo
• dicee — Dice embedding is an hardware-agnostic framework for large-scale knowledge graph embedding applications
• diffnovo — DiffNovo: A Transformer-Diffusion Model for De Novo Peptide Sequencing
• diffusionlab — Easy no-frills Pytorch implementations of common abstractions for diffusion models.
• directmultistep — no summary
• disent — Vae disentanglement framework built with pytorch lightning.
• dlhpcstarter — Deep Learning and HPC Starter Pack
• dlk — dlk: Deep Learning Kit
• dmri-pcconv — Parametric Continuous Convolution framework used for Diffusion MRI.
• dmt-learn — An Explainable Deep Network for Dimension Reduction (EVNet)
• dreamai-dl — Deep Learning tools based on dreamai.
• drvi-py — Disentangled Generative Representation of Single Cell Omics
• dsbundle — Streamline your data science setup with dsbundle in one effortless install.
• dtrc — data torch
• dummy-problems — Solving simple problems using machine learning
• dvclive — Experiments logger for ML projects.
• e2efs — E2E-FS Feature Selection Method
• eegpp2-beta — EEG Phrase Predictor ver 2
• eir-dl — Deep learning framework for genomics and multi-modal data
• encyclopedia-vae — Add your description here
• esm-efficient — Efficient Evolutionary Scale Modeling: Efficient and simplified implementation of protein language model for inference and training.
• etflow — Equivariant Flow Matching for Molecular Conformer Generation
• ezformer — Run enformer like models, get prediction tracks, and perform benchmarking
• f9ml — JSI F9 machine learning framework.
• fastai — fastai simplifies training fast and accurate neural nets using modern best practices
• fastprop — Fast Molecular Property Prediction with mordredcommunity
• fauasg — A set of tools developed by the Animal Speech Group at FAU
• finetuning-scheduler — A PyTorch Lightning extension that enhances model experimentation with flexible fine-tuning schedules.
• fintorch — AI4FinTech project repository
• flexynesis — A deep-learning based multi-omics bulk sequencing data integration suite with a focus on (pre-)clinical endpoint prediction.
• flowcean — Automatic generation of models for cyber-physical systems.
• fodnet — FOD-Net Reimplementation.