QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

Overview

QuickAI logo

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

Announcement video https://www.youtube.com/watch?v=kK46sJphjIs

Motivation

When I started to get into more advanced Machine Learning, I started to see how these famous neural network architectures(such as EfficientNet), were doing amazing things. However, when I tried to implement these architectures to problems that I wanted to solve, I realized that it was not super easy to implement and quickly experiment with these architectures. That is where QuickAI came in. It allows for easy experimentation of many model architectures quickly.

Dependencies:

Tensorflow, PyTorch, Sklearn, Matplotlib, Numpy, and Hugging Face Transformers. You should install TensorFlow and PyTorch following the instructions from their respective websites.

Why you should use QuickAI

QuickAI can reduce what would take tens of lines of code into 1-2 lines. This makes fast experimentation very easy and clean. For example, if you wanted to train EfficientNet on your own dataset, you would have to manually write the data loading, preprocessing, model definition and training code, which would be many lines of code. Whereas, with QuickAI, all of these steps happens automatically with just 1-2 lines of code.

The following models are currently supported:

  1. Image Classification

    • EfficientNet B0-B7
    • VGG16
    • VGG19
    • DenseNet121
    • DenseNet169
    • DenseNet201
    • Inception ResNet V2
    • Inception V3
    • MobileNet
    • MobileNet V2
    • MobileNet V3 Small & Large
    • ResNet 101
    • ResNet 101 V2
    • ResNet 152
    • ResNet 152 V2
    • ResNet 50
    • ResNet 50 V2
    • Xception
  2. Natural Language Processing

    • GPT-NEO 125M(Generation, Inference)
    • GPT-NEO 350M(Generation, Inference)
    • GPT-NEO 1.3B(Generation, Inference)
    • GPT-NEO 2.7B(Generation, Inference)
    • Distill BERT Cased(Q&A, Inference and Fine Tuning)
    • Distill BERT Uncased(Named Entity Recognition, Inference)
    • Distil BART (Summarization, Inference)
    • Distill BERT Uncased(Sentiment Analysis & Text/Token Classification, Inference and Fine Tuning)

Installation

pip install quickAI

How to use

Please see the examples folder for details.

Issues/Questions

If you encounter any bugs, please open a new issue so they can be corrected. If you have general questions, please use the discussion section.

Comments
  • Memory error

    Memory error

    Is it possible to host the gpt neo models on a website and make some kind of API, the models are to large to run on my computer. Also It would be nice if to have a stop function so the model knows at what token to stop and be able to add examples of the query needed.

    enhancement 
    opened by TheProtaganist 5
  • Add link to a demo

    Add link to a demo

    Hi, I tried using the notebook in the example folder but it wasn't working (I think the files were not imported into Colab), so I created a demo which should work.

    opened by equiet 1
  • Better code for image_classification.py

    Better code for image_classification.py

    Main change: Used a dict instead of excessive elifs. Other smaller changes.

    Important: I do not have the resources to test the code, but technically, it's just a rewrite of the original, so it should work.

    opened by pinjuf 1
  • [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    This PR was automatically created by Snyk using the credentials of a real user.


    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires numpy, which is not installed.
    torchvision 0.5.0 requires pillow, which is not installed.
    sympy 1.5.1 requires mpmath, which is not installed.
    coremltools 6.0 requires numpy, which is not installed.
    coremltools 6.0 requires protobuf, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 551/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.3 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-WHEEL-3092128 | wheel:
    0.30.0 -> 0.38.0
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Regular Expression Denial of Service (ReDoS)

    opened by geekjr 0
  • [Snyk] Security upgrade ubuntu from 21.10 to jammy

    [Snyk] Security upgrade ubuntu from 21.10 to jammy

    This PR was automatically created by Snyk using the credentials of a real user.


    Keeping your Docker base image up-to-date means you’ll benefit from security fixes in the latest version of your chosen image.

    Changes included in this PR

    • Dockerfile

    We recommend upgrading to ubuntu:jammy, as this image has only 10 known vulnerabilities. To do this, merge this pull request, then verify your application still works as expected.

    Some of the most important vulnerabilities in your base image include:

    | Severity | Priority Score / 1000 | Issue | Exploit Maturity | | :------: | :-------------------- | :---- | :--------------- | | medium severity | 514 | Out-of-bounds Read
    SNYK-UBUNTU2110-E2FSPROGS-2770726 | No Known Exploit | | medium severity | 300 | NULL Pointer Dereference
    SNYK-UBUNTU2110-KRB5-1735754 | No Known Exploit | | medium severity | 300 | OS Command Injection
    SNYK-UBUNTU2110-OPENSSL-2933132 | No Known Exploit | | medium severity | 300 | Inadequate Encryption Strength
    SNYK-UBUNTU2110-OPENSSL-2941384 | No Known Exploit | | medium severity | 300 | Improper Verification of Cryptographic Signature
    SNYK-UBUNTU2110-PERL-1930909 | No Known Exploit |


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Learn about vulnerability in an interactive lesson of Snyk Learn.

    opened by geekjr 0
  • [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    This PR was automatically created by Snyk using the credentials of a real user.


    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    sympy 1.5.1 requires mpmath, which is not installed.
    coremltools 6.0 requires protobuf, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 551/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.3 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-WHEEL-3092128 | wheel:
    0.30.0 -> 0.38.0
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Regular Expression Denial of Service (ReDoS)

    opened by geekjr 0
  • [Snyk] Security upgrade protobuf from 3.20.1 to 3.20.2

    [Snyk] Security upgrade protobuf from 3.20.1 to 3.20.2

    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    sympy 1.5.1 requires mpmath, which is not installed.
    coremltools 6.0 requires protobuf, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 571/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.7 | Denial of Service (DoS)
    SNYK-PYTHON-PROTOBUF-3031740 | protobuf:
    3.20.1 -> 3.20.2
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Learn about vulnerability in an interactive lesson of Snyk Learn.

    opened by snyk-bot 0
  • [Snyk] Security upgrade ubuntu from rolling to 21.10

    [Snyk] Security upgrade ubuntu from rolling to 21.10

    Keeping your Docker base image up-to-date means you’ll benefit from security fixes in the latest version of your chosen image.

    Changes included in this PR

    • Dockerfile

    We recommend upgrading to ubuntu:21.10, as this image has only 12 known vulnerabilities. To do this, merge this pull request, then verify your application still works as expected.

    Some of the most important vulnerabilities in your base image include:

    | Severity | Issue | Exploit Maturity | | :------: | :---- | :--------------- | | medium severity | Improper Verification of Cryptographic Signature
    SNYK-UBUNTU2110-PERL-1930909 | No Known Exploit | | low severity | Time-of-check Time-of-use (TOCTOU)
    SNYK-UBUNTU2110-SHADOW-1758374 | No Known Exploit | | low severity | Time-of-check Time-of-use (TOCTOU)
    SNYK-UBUNTU2110-SHADOW-1758374 | No Known Exploit | | low severity | NULL Pointer Dereference
    SNYK-UBUNTU2110-TAR-1744334 | No Known Exploit | | medium severity | CVE-2018-25032
    SNYK-UBUNTU2110-ZLIB-2433596 | No Known Exploit |


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Learn about vulnerability in an interactive lesson of Snyk Learn.

    opened by snyk-bot 0
  • [Snyk] Security upgrade ubuntu from 18.04 to rolling

    [Snyk] Security upgrade ubuntu from 18.04 to rolling

    Keeping your Docker base image up-to-date means you’ll benefit from security fixes in the latest version of your chosen image.

    Changes included in this PR

    • Dockerfile

    We recommend upgrading to ubuntu:rolling, as this image has only 13 known vulnerabilities. To do this, merge this pull request, then verify your application still works as expected.

    Some of the most important vulnerabilities in your base image include:

    | Severity | Priority Score / 1000 | Issue | Exploit Maturity | | :------: | :-------------------- | :---- | :--------------- | | medium severity | 300 | Information Exposure
    SNYK-UBUNTU1804-GCC8-572149 | No Known Exploit | | medium severity | 300 | Information Exposure
    SNYK-UBUNTU1804-GCC8-572149 | No Known Exploit | | medium severity | 300 | Information Exposure
    SNYK-UBUNTU1804-GCC8-572149 | No Known Exploit | | medium severity | 300 | Improper Verification of Cryptographic Signature
    SNYK-UBUNTU1804-PERL-1930908 | No Known Exploit | | low severity | 150 | Time-of-check Time-of-use (TOCTOU)
    SNYK-UBUNTU1804-SHADOW-306209 | No Known Exploit |


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Learn about vulnerability in an interactive lesson of Snyk Learn.

    opened by snyk-bot 0
  • [Snyk] Security upgrade numpy from 1.19.5 to 1.22.0

    [Snyk] Security upgrade numpy from 1.19.5 to 1.22.0

    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- low severity | 471/1000
    Why? Recently disclosed, Has a fix available, CVSS 3.7 | Buffer Overflow
    SNYK-PYTHON-NUMPY-2321966 | numpy:
    1.19.5 -> 1.22.0
    | No | No Known Exploit low severity | 578/1000
    Why? Proof of Concept exploit, Recently disclosed, Has a fix available, CVSS 3.7 | Buffer Overflow
    SNYK-PYTHON-NUMPY-2321969 | numpy:
    1.19.5 -> 1.22.0
    | No | Proof of Concept low severity | 578/1000
    Why? Proof of Concept exploit, Recently disclosed, Has a fix available, CVSS 3.7 | Denial of Service (DoS)
    SNYK-PYTHON-NUMPY-2321970 | numpy:
    1.19.5 -> 1.22.0
    | No | Proof of Concept

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the effected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic

    opened by snyk-bot 0
  • [Snyk] Security upgrade numpy from 1.19.5 to 1.22.0rc1

    [Snyk] Security upgrade numpy from 1.19.5 to 1.22.0rc1

    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- low severity | 578/1000
    Why? Proof of Concept exploit, Recently disclosed, Has a fix available, CVSS 3.7 | Buffer Overflow
    SNYK-PYTHON-NUMPY-2321969 | numpy:
    1.19.5 -> 1.22.0rc1
    | No | Proof of Concept low severity | 578/1000
    Why? Proof of Concept exploit, Recently disclosed, Has a fix available, CVSS 3.7 | Denial of Service (DoS)
    SNYK-PYTHON-NUMPY-2321970 | numpy:
    1.19.5 -> 1.22.0rc1
    | No | Proof of Concept

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the effected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic

    opened by snyk-bot 0
  • [Snyk] Security upgrade setuptools from 39.0.1 to 65.5.1

    [Snyk] Security upgrade setuptools from 39.0.1 to 65.5.1

    This PR was automatically created by Snyk using the credentials of a real user.


    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    sympy 1.5.1 requires mpmath, which is not installed.
    coremltools 6.1 requires protobuf, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 551/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.3 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-SETUPTOOLS-3180412 | setuptools:
    39.0.1 -> 65.5.1
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Regular Expression Denial of Service (ReDoS)

    opened by geekjr 0
  • [Snyk] Security upgrade setuptools from 39.0.1 to 65.5.1

    [Snyk] Security upgrade setuptools from 39.0.1 to 65.5.1

    This PR was automatically created by Snyk using the credentials of a real user.


    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires numpy, which is not installed.
    torchvision 0.5.0 requires pillow, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- low severity | 441/1000
    Why? Recently disclosed, Has a fix available, CVSS 3.1 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-SETUPTOOLS-3113904 | setuptools:
    39.0.1 -> 65.5.1
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Regular Expression Denial of Service (ReDoS)

    opened by geekjr 0
  • [Snyk] Security upgrade protobuf from 3.20.1 to 3.20.2

    [Snyk] Security upgrade protobuf from 3.20.1 to 3.20.2

    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    sympy 1.5.1 requires mpmath, which is not installed.
    coremltools 6.0 requires protobuf, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 571/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.7 | Denial of Service (DoS)
    SNYK-PYTHON-PROTOBUF-3031740 | protobuf:
    3.20.1 -> 3.20.2
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Learn about vulnerability in an interactive lesson of Snyk Learn.

    opened by snyk-bot 0
Releases(2.0.0)
Official PyTorch implementation of "BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation" (NeurIPS 2021)

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation Official PyTorch implementation of the NeurIPS 2021 paper Mingcong Liu, Qiang

onion 462 Dec 29, 2022
The pytorch implementation of SOKD (BMVC2021).

Semi-Online Knowledge Distillation Implementations of SOKD. Requirements This repo was tested with Python 3.8, PyTorch 1.5.1, torchvision 0.6.1, CUDA

4 Dec 19, 2021
Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models

Face Recognition Using Pytorch Python 3.7 3.6 3.5 Status This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and

Tim Esler 3.3k Jan 04, 2023
Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN", accepted to ACM MM 2021 BNI Track.

RecycleD Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN

Yunan Zhu 23 Nov 05, 2022
Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”

VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto

120 Jan 06, 2023
How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach

EV-charging-impact This repository contains the code that has been used for the Queue modelling for the paper "How will electric vehicles affect traff

7 Nov 30, 2022
Minimalist Error collection Service compatible with Rollbar clients. Sentry or Rollbar alternative.

Minimalist Error collection Service Features Compatible with any Rollbar client(see https://docs.rollbar.com/docs). Just change the endpoint URL to yo

Haukur Rósinkranz 381 Nov 11, 2022
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

30 Nov 14, 2022
Minimalistic PyTorch training loop

Backbone for PyTorch training loop Will try to keep it minimalistic. pip install back from back import Bone Features Progress bar Checkpoints saving/l

Kashin 4 Jan 16, 2020
Voxel-based Network for Shape Completion by Leveraging Edge Generation (ICCV 2021, oral)

Voxel-based Network for Shape Completion by Leveraging Edge Generation This is the PyTorch implementation for the paper "Voxel-based Network for Shape

10 Dec 04, 2022
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis

A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Figure: Shape-Accurate 3D-Aware Image Synthesis. A Shading-Guid

Xingang Pan 115 Dec 18, 2022
A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation.

Continuous Wasserstein-2 Benchmark This is the official Python implementation of the NeurIPS 2021 paper Do Neural Optimal Transport Solvers Work? A Co

Alexander 22 Dec 12, 2022
A command line simple note taking app

Why yet another note taking program? note was designed with a very specific target in mind: me, and my 2354 scraps of paper. It runs from the command

64 Nov 20, 2022
Python script that allows you to automatically setup your Growtopia server.

AutoSetup Python script that allows you to automatically setup your Growtopia server. How To Use Firstly, install all the required modules that used i

Aspire 3 Mar 06, 2022
Tacotron 2 - PyTorch implementation with faster-than-realtime inference

Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati

NVIDIA Corporation 4.1k Jan 03, 2023
[内测中]前向式Python环境快捷封装工具,快速将Python打包为EXE并添加CUDA、NoAVX等支持。

QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具,最短只需一行命令即可将普通的Python脚本打包成EXE可执行程序,并选择性添加CUDA和NoAVX的支持,尽可能兼容更多的用户环境。 感觉还可

QPT Family 545 Dec 28, 2022
Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"

NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B

Bee Lim 625 Dec 30, 2022
Demonstrates iterative FGSM on Apple's NeuralHash model.

apple-neuralhash-attack Demonstrates iterative FGSM on Apple's NeuralHash model. TL;DR: It is possible to apply noise to CSAM images and make them loo

Lim Swee Kiat 11 Jun 23, 2022
Rank1 Conversation Emotion Detection Task

Rank1-Conversation_Emotion_Detection_Task accuracy macro-f1 recall 0.826 0.7544 0.719 基于预训练模型和时序预测模型的对话情感探测任务 1 摘要 针对对话情感探测任务,本文将其分为文本分类和时间序列预测两个子任务,分

Yuchen Han 2 Nov 28, 2021
CONditionals for Ordinal Regression and classification in PyTorch

CONDOR pytorch implementation for ordinal regression with deep neural networks. Documentation: https://GarrettJenkinson.github.io/condor_pytorch About

7 Jul 25, 2022