A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

ParlAI (pronounced “par-lay”) is a framework for dialog AI research, implemented in Python. Its goal is to provide researchers: a unified framework for sharing, training and testing dialog models multi-task training over many dat

Related Repos



mantra-inc OpenMantra dataset is a evaluation dataset for machine translation of manga. The dataset comprised of five Japanese manga series across different genres, including fantasy, romance, battle, mystery, and slice of life. Original Japanese texts are translated into English and Chinese by professional translator.
 

THUMNLab AutoGL is developed for researchers and developers to quickly conduct autoML on the graph datasets & tasks. See our documentation for detailed information!
 

ebagdasa Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
 

victor369basu In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model architecture, and Kafka for real-time data streaming and pipelining.
 

jsoma Persine is an automated tool to study and reverse-engineer algorithmic recommendation systems. It has a simple interface and encourages reproducible results.
 

facebookresearch TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors
 

lucidrains Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed their group to outperform all previous methods in point cloud classification and segmentation.
 

Rishit-dagli This repository shows the TFJS model conversion and inference processes for the for the MIRNet model as proposed by Learning Enriched Features for Real Image Restoration and Enhancement by Zamir et al. This model is capable of enhancing low-light images upto a great extent.