Search Results for "ai research" - Page 7
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Showing 210 open source projects for "ai research"
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LaMDA-pytorch
Open-source pre-training implementation of Google's LaMDA in PyTorch
Open-source pre-training implementation of Google's LaMDA research paper in PyTorch. The totally not sentient AI. This repository will cover the 2B parameter implementation of the pre-training architecture as that is likely what most can afford to train. You can review Google's latest blog post from 2022 which details LaMDA here. You can also view their previous blog post from 2021 on the model. -
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ruDALL-E
Generate images from texts. In Russian
...You can even combine different languages within a single query. This neural network has been developed and trained by Sber AI researchers in close collaboration with scientists from Artificial Intelligence Research Institute using joined datasets by Sber AI and SberDevices. Russian text-to-image model that generates images from text. The architecture is the same as ruDALL-E XL. Even more parameters in the new version. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the... -
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GLIDE (Text2Im)
GLIDE: a diffusion-based text-conditional image synthesis model
...The project also offers sampling scripts and utilities for exploring how diffusion models can be applied to multimodal tasks. As one of the early diffusion-based text-to-image systems, glide-text2im laid important groundwork for later advances in generative AI research. -
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RLCard
Reinforcement Learning / AI Bots in Card (Poker) Games
RLCard is a toolkit for reinforcement learning research on card games. It includes several popular card games and focuses on learning algorithms for imperfect information games like poker and blackjack. -
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PaddleGAN
PaddlePaddle GAN library, including lots of interesting applications
...GAN-Generative Adversarial Network, was praised by "the Father of Convolutional Networks" Yann LeCun (Yang Likun) as [One of the most interesting ideas in the field of computer science in the past decade]. It's the one research area in deep learning that AI researchers are most concerned about. -
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GiantMIDI-Piano
Classical piano MIDI dataset
...It provides a resource for music information retrieval (MIR), symbolic music modeling, composer classification, music generation, analysis of classical piano repertoire, and data-driven research in musicology or AI-based composition. Because the dataset is machine-generated via an automated transcription pipeline, it offers consistency, scale, and accessibility that would be difficult to achieve manually — enabling researchers to work with large corpora of piano music without copyright restrictions on symbolic data. -
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MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation
MaskFormer is a unified framework for image segmentation developed by Facebook Research, designed to bridge the gap between semantic, instance, and panoptic segmentation within a single architecture. Unlike traditional segmentation pipelines that treat these tasks separately, MaskFormer reformulates segmentation as a mask classification problem, enabling a consistent and efficient approach across multiple segmentation domains. Built on top of Detectron2, it supports a wide range of datasets... -
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MuJoCo-py
mujoco-py allows using MuJoCo from Python 3
mujoco-py is a Python wrapper for MuJoCo, a high-performance physics engine widely used in robotics, reinforcement learning, and AI research. It allows developers and researchers to run detailed rigid body simulations with contacts directly from Python, making MuJoCo easier to integrate into machine learning workflows. The library is compatible with MuJoCo version 2.1 and supports Linux and macOS, while Windows support has been deprecated. It provides utilities for loading models, running simulations, and accessing simulation states in real time, along with visualization tools for rendering environments. ... -
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TorchGAN
Research Framework for easy and efficient training of GANs
The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to... -
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. -
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hebrew-gpt_neo
Hebrew text generation models based on EleutherAI's gpt-neo
Hebrew text generation models based on EleutherAI's gpt-neo. Each was trained on a TPUv3-8 which was made available to me via the TPU Research Cloud Program. The Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy architecture. -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. ... -
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FixRes
Reproduces results of "Fixing the train-test resolution discrepancy"
FixRes is a lightweight yet powerful training methodology for convolutional neural networks (CNNs) that addresses the common train-test resolution discrepancy problem in image classification. Developed by Facebook Research, FixRes improves model generalization by adjusting training and evaluation procedures to better align input resolutions used during different phases. The approach is simple but highly effective, requiring no architectural modifications and working across diverse CNN... -
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Image GPT
Large-scale autoregressive pixel model for image generation by OpenAI
Image-GPT is the official research code and models from OpenAI’s paper Generative Pretraining from Pixels. The project adapts GPT-2 to the image domain, showing that the same transformer architecture can model sequences of pixels without altering its fundamental structure. It provides scripts to download pretrained checkpoints of different model sizes (small, medium, large) trained on large-scale datasets and includes utilities for handling color quantization with a 9-bit palette.... -
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Multi-Agent Emergence Environments
Environment generation code for the paper "Emergent Tool Use"
multi-agent-emergence-environments is an open source research environment framework developed by OpenAI for the study of emergent behaviors in multi-agent systems. It was designed for the experiments described in the paper and blog post “Emergent Tool Use from Multi-Agent Autocurricula”, which investigated how complex cooperative and competitive behaviors can evolve through self-play. The repository provides environment generation code that builds on the mujoco-worldgen package, enabling... -
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a model-oriented library designed to showcase novel and different neural network optimizations. The library contains NLP/NLU-related models per task, different neural network topologies (which are used in models), procedures for simplifying workflows in the library, pre-defined data processors and dataset loaders and misc utilities. ... -
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HyperGAN
Composable GAN framework with api and user interface
A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with... -
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GPT2 for Multiple Languages
GPT2 for Multiple Languages, including pretrained models
With just 2 clicks (not including Colab auth process), the 1.5B pretrained Chinese model demo is ready to go. The contents in this repository are for academic research purpose, and we do not provide any conclusive remarks. Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC) Simplifed GPT2 train scripts（based on Grover, supporting TPUs). Ported bert tokenizer, multilingual corpus compatible. 1.5B GPT2 pretrained Chinese model (~15G corpus, 10w steps).... -
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PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
PyTorch GAN Zoo is a comprehensive open research toolbox designed for experimenting with and developing Generative Adversarial Networks (GANs) using PyTorch. The project provides modular implementations of popular GAN architectures, including Progressive Growing of GANs (PGAN), DCGAN, and an experimental StyleGAN version. It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD,... -
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End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the... -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. ...
