Reverse Dependencies of hydra-core
The following projects have a declared dependency on hydra-core:
- mlops-ods — no summary
- mloq — Package for initializing ML projects following ML Ops best practices.
- MLXP — A framework for conducting machine learning experiments in python
- moai-hydra-searchpath-plugin — moai Hydra SearchPath plugin
- moai-mdk — moai: Accelerated, Flexible, Modular, Reproducible, Insightful AI
- monet-pytorch — Pytorch implementation of Multi-Object Network(MONet)
- motrack — Tracking-by-detection (MOT) package
- move-dl — Multi-omics variational autoencoder
- mqtts-lightning — Add a short description here
- mridc — Data Consistency for Magnetic Resonance Imaging
- mtrl — MTRL: Multi Task RL Algorithms
- multibeast — no summary
- MultiEL — Multilingual Entity Linking model by BELA model
- multiviewae — A library for running multiview autoencoder models
- narg2p — Non AutoRegressive Grapheme to Phoneme conversion Toolkit
- nemo-toolkit — NeMo - a toolkit for Conversational AI
- neoconfigen — A fork of hydra-core's configen with extended type-compatibility.
- nested-ragged-tensors — Utilities for efficiently working with, saving, and loading, collections of connected nested ragged tensors in PyTorch
- nett-bd — A small example package
- niceml — Welcome to niceML 🍦, a Python-based MLOps framework that uses TensorFlow and Dagster. This framework streamlines the development, and maintenance of machine learning models, providing an end-to-end solution for building efficient and scalable pipelines.
- nlhappy — 自然语言处理(NLP)
- nn-template-core — Utility library for nn-template.
- nnabla-nas — Use NNC compute resource from NNabla
- nnsmith — "Automatic DNN generation for fuzzing and more."
- noisebase — Datasets and benchmarks for neural Monte Carlo denoising
- nrslib — Standardised Library for the Benchmarking of News Recommenders Systems
- nvidia-modulus — A deep learning framework for AI-driven multi-physics systems
- nvidia-modulus.launch — Optimized tranining recipes for accelerating PyTorch workflows of AI driven surrogates for physical systems
- nvidia-modulus.sym — A deep learning framework for AI-driven multi-physics systems
- nvidia-tao-deploy — NVIDIA's package for deploying models from TAO Toolkit.
- omniverse — A collection of code for Omniverse.
- oneat — Action classification for TZYX/TYX shaped images, Static classification for TYX/YX shaped images
- open-metric-learning — OML is a PyTorch-based framework to train and validate the models producing high-quality embeddings.
- openbb-chat — Deep learning package to add chat capabilities to OpenBB
- OpenELM — Evolution Through Large Models
- OpenHands — 👐OpenHands : Making Sign Language Recognition Accessible
- openkiwi — Machine Translation Quality Estimation Toolkit
- openpack-torch — PyTorch extention to work around with OpenPack dataset
- openspeech-core — Open-Source Toolkit for End-to-End Automatic Speech Recognition
- openspeech-py — Open-Source Toolkit for End-to-End Automatic Speech Recognition
- openspeechs — Open-Source Toolkit for End-to-End Automatic Speech Recognition
- paddlesci — A library for scientific machine learning
- palkit — Useful functions.
- pandassta — Package for easy datarequests from sensortings
- pansharpening — Deep learning for pansharpening in remote sensing
- parlai — Unified platform for dialogue research.
- pdebench — PDEBench: An Extensive Benchmark for Scientific Machine Learning
- pedl — Search the biomedical literature for protein interactions andprotein associations.
- phalp — PHALP: A Python package for People Tracking in 3D
- pipeline-feature — Feature Pipeline of MLOps Pipeline Version 1
- pixellib — PixelLib is a library used for easy implementation of semantic and instance segmentation of objects in images and videos with few lines of code.PixelLib makes it possible to train a custom segmentation model using few lines of code.PixelLib supports background editing of images and videos using few lines of code.
- power-cogs — A set of useful research templates for deep learning projects
- prodsys — A useful module for production system simulation and optimization
- propinfer — Modular framework to run Property Inference Attacks on Machine Learning models.
- proteinworkshop — no summary
- provision-ai — AI experiment provisioner
- pugh-torch — Functions, losses, and module blocks to share between experiments.
- PVNet — PVNet
- PVNet-summation — Package for training summation model for PVNet
- pyannote.audio — Neural building blocks for speaker diarization
- pyclarity — Tools for the Clarity Challenge
- pycyclops — Framework for healthcare ML implementation
- pyrovelocity — A multivariate RNA Velocity model to estimate future cell states with uncertainty using probabilistic modeling with pyro.
- pytorch-caldera — no summary
- pytorch-cortex — A modular architecture for deep learning systems.
- pytorch-lightning — PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.
- pytorch-segmentation-models-trainer — Image segmentation models training of popular architectures.
- pytorch-yard — PyTorch experiment runner
- pytorch3d — PyTorch3D is FAIR's library of reusable components for deep Learning with 3D data.
- pytouch — A PyTorch library for tactile touch sensing.
- qai-hub-models — Models optimized for export to run on device.
- quke — Compare the answering capabilities of different LLMs - for example LlaMa, ChatGPT, Cohere, Falcon - against user provided document(s) and questions.
- ranzen — A toolkit facilitating machine-learning experimentation.
- rats-processors — Rats Processors
- regulAS — Bioinformatics Tool for the Integrative Analysis of Alternative Splicing Regulome using RNA-Seq data
- reinventing-catastrophe-modelling — no summary
- removesalt — Add a short description here!
- retexture — ReTexture dataset toolkit for generation and analysis
- rl4co — RL4CO: a Unified Reinforcement Learning for Combinatorial Optimization Library
- rna — Basic and essential code building blocks of all pythons
- rocks-classifier — Rock classifier deployed on railway and monitored using Weights and Biases!
- rofunc — Full-process robot learning from demonstration package
- rtk-mult-clf — no summary
- rul-adapt — A collection of unsupervised domain adaption approaches for RUL estimation.
- ruprompts — Fast prompt tuning framework for large language models
- rxn-reaction-preprocessing — Reaction preprocessing tools
- sail-on-client — Client and Protocols for DARPA sail-on
- satflow — Satellite Optical Flow
- scalingtheunet — This project is the source code to our paper.
- schnetpack — SchNetPack - Deep Neural Networks for Atomistic Systems
- SciAssist — A toolkit for Scientific Document Processing
- scope-rl — SCOPE-RL: A pipeline for offline reinforcement learning research and applications
- scyan — Single-cell Cytometry Annotation Network
- sequel-core — A Continual Learning Framework for both Jax and PyTorch.
- serotiny — A framework of tools to structure, configure and drive deep learning projects
- sf-grid — General Robot Intelligence Development platform.
- sheeprl — High-quality, single file and distributed implementation of Deep Reinforcement Learning algorithms with production-friendly features
- sherpa-ai — Sherpa: AI-augmented thinking companion
- shrike — Python utilities for compliant Azure machine learning
- sim-web-visualizer — Web based visualizer for simulators