May 24, 2021 Advanced, Artificial intelligence, Deep Learning, NLP, PyTorch

BERT for Natural Language Inference simplified in Pytorch!

This article was published as a part of the Data Science Blogathon Introduction to BERT: BERT stands for Bidirectional Encoder Representations from Transformers. It was introduced in 2018 by Google Researchers. BERT achieved state-of-art performance in most of the NLP tasks at that time and drawn the attention of the data science community worldwide. It is extensively used today by data science practitioners for various NLP tasks. Details about the working of the BERT model can be found here. Introduction to […]

May 23, 2021 NLP

A Time-Domain Convolutional Recurrent Network for Packet Loss Concealment

Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong […]

May 23, 2021 Machine Learning

An all-MLP replacement for Transformers in Pytorch

gMLP – Pytorch Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch Install $ pip install g-mlp-pytorch Usage For masked language modelling import torch from g_mlp_pytorch import gMLP model = gMLP( num_tokens = 20000, dim = 512, depth = 6, seq_len = 256 ) x = torch.randint(0, 20000, (1, 256)) logits = model(x) # (1, 256, 20000) For image classification import torch from g_mlp_pytorch import gMLPVision model = gMLPVision( image_size = 256, patch_size = 16, num_classes = 1000, dim […]

May 23, 2021 Video

Contact and Human Dynamics from Monocular Video

This is the official implementation for the ECCV 2020 spotlight paper by Davis Rempe, Leonidas J. Guibas, Aaron Hertzmann, Bryan Russell, Ruben Villegas, and Jimei Yang. For more information, see the project webpage. Environment Setup Note: the code in this repo has only been tested on Ubuntu 16.04. First create and activate a virtual environment to install dependencies for the code in this repo. For example with conda: conda create -n contact_dynamics_env python=3.6 conda activate contact_dynamics_env pip install -r requirements.txt […]

May 23, 2021 Deep Learning

A collection of pretrained models in Flax

Flax Models The goal of this project is to make current deep learning models more easily available for the awesome Jax/Flax ecosystem. Models Example Notebooks to play with on Colab Installation You will need Python 3.7 or later. For GPU usage, follow the Jax installation with CUDA. Then install: > pip install –upgrade git+https://github.com/matthias-wright/flaxmodels.git For CPU-only you can skip step 1. Documentation The documentation for the models can be found here. Checkpoints The checkpoints are taken from the repositories that […]

May 23, 2021 RESTful API

An iNaturalist API client for python

pyinaturalist Pyinaturalist is an iNaturalist API client for python. Features iNaturalist offers a rich source of biodiversity data, and an extensive API to interact with it. If you want to make use of these data in python, then pyinaturalist can help! It adds a number of python-specific conveniences, including: Requests: Simplified usage with python types and data structures Responses: Type conversions to things you would expect in python Server-Friendly Usage: Client-side rate-limiting that follows the API Recommended Practices Typing: Complete […]

May 23, 2021 Command-line Tools

Command-line tool for managing Python virtual environments

vien VIEN is a command-line tool for managing Python Virtual Environments. It provides one-line shortcuts for: creating and deleting environments running commands inside environments switching between environments in bash shell Switching between projects should be simple. Creating environments for theprojects should be simple too. Ideally it’s a short command that I would type even half asleep. Something like $ vien create $ vien shell Not like $ python3 -m venv ./where/to/put/this/.venv $ source /i/lost/that/.venv/bin/activate Ready-made solutions did not help. pipenv […]

May 23, 2021 Tool

An OSINT tool written in python for finding profiles by username

NExfil NExfil is an OSINT tool written in python for finding profiles by username. The provided usernames are checked on over 350 websites within few seconds. The goal behind this tool was to get results quickly while maintaining low amounts of false positives. If you like my work please star this project 😀 If you find any errors or false positives or if you want to suggest more websites feel free to open an issue. Features Fast, lookup can complete […]

May 23, 2021 Network

A social networking service scraper in Python

snscrape is a scraper for social networking services (SNS). It scrapes things like user profiles, hashtags, or searches and returns the discovered items, e.g. the relevant posts. The following services are currently supported: Facebook: user profiles, groups, and communities (aka visitor posts) Instagram: user profiles, hashtags, and locations Reddit: users, subreddits, and searches (via Pushshift) Telegram: channels Twitter: users, user profiles, hashtags, searches, threads, and list posts VKontakte: user profiles Weibo (Sina Weibo): user profiles Please note that some features […]

May 23, 2021 Command-line Tools

A library for building CLI applications Based on Python type hints

typer Typer, build great CLIs. Easy to code. Based on Python type hints. Typer is a library for building CLI applications that users will love using and developers will love creating. Based on Python 3.6+ type hints. The key features are: Intuitive to write: Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Easy to use: It’s easy to use for the final users. Automatic help, and automatic completion […]

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