Top 23 Python Pytorch Projects
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.Latest mention: Confidence score prediction of huggingface transformers' models for extractive QA task | reddit.com/r/LanguageTechnology | 2020-12-27
Clone a voice in 5 seconds to generate arbitrary speech in real-timeLatest mention: I used AI tools to generate audio of SpongeBob rapping a portion of "Gangster's Paradise" | reddit.com/r/videos | 2021-01-05
I've been struggling to get this https://github.com/CorentinJ/Real-Time-Voice-Cloning to work. But I always get stuck on mis-matching python libraries.
PyTorch Tutorial for Deep Learning ResearchersLatest mention: [P] Probabilistic Machine Learning: An Introduction, Kevin Murphy's 2021 e-textbook is out | reddit.com/r/MachineLearning | 2021-01-01
Image-to-Image Translation in PyTorchLatest mention: This Wojak Does Not Exist | news.ycombinator.com | 2020-12-31
OpenMMLab Detection Toolbox and BenchmarkLatest mention: [D] How to organize deep learning projects on Github ? | reddit.com/r/MachineLearning | 2021-01-10
You can check these repos: https://github.com/open-mmlab/mmdetection https://github.com/facebookresearch/detectron2
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.Latest mention: Weekly Developer Roundup #23 - Sun Nov 22 2020 | dev.to | 2020-11-21
PyTorchLightning/pytorch-lightning (Python): The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.Latest mention: Top 10 Developer Trends, Thu Oct 22 2020 | dev.to | 2020-10-22
pytorch / fairseq
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.Latest mention: Top 10 Developer Trends, Sun Oct 18 2020 | dev.to | 2020-10-18
microsoft / nni
YOLOv5 in PyTorch > ONNX > CoreML > TFLiteLatest mention: Yolov5x | reddit.com/r/computervision | 2021-01-06
Yes, it is trained on COCO. All the codes are from this repo https://github.com/ultralytics/yolov5
Bringing Old Photo Back to Life (CVPR 2020 oral)Latest mention: Weekly Developer Roundup #23 - Sun Nov 22 2020 | dev.to | 2020-11-21
microsoft/Bringing-Old-Photos-Back-to-Life (Python): Bringing Old Photo Back to Life (CVPR 2020 oral)
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation toolsLatest mention: [P] 611 text datasets in 467 languages in the new v1.2 release of HuggingFace datasets library | reddit.com/r/MachineLearning | 2021-01-05
There will be 13 more bytthe end of this week, from Microsoft CodeXGlue, I had not the time to fix my PR earlier : https://github.com/huggingface/datasets/pull/997 .
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.Latest mention: Apple’s New M1 Chip is a Machine Learning Beast | reddit.com/r/apple | 2020-12-25
Yes. But that's missing the point. Almost everything in the space uses a framework other than Core ML. Therefore most people need good development support for PyTorch/Tensorflow etc., not Core ML. The fact that Apple has a tool to import/convert models is nice, but not relevant. Also, there is onnx as an exchange format between the frameworks, and tools like MMdnn and others.
Official Stanford NLP Python Library for Many Human Languages
Open Source Differentiable Computer Vision Library for PyTorch
End-to-End Speech Processing ToolkitLatest mention: Downpour: DRM Free Audiobooks | news.ycombinator.com | 2021-01-17
I really like google text to speech and use it for my own custom audiobooks, I've tried google's microsoft's, IBM's, and a few other research ones. IBM's sounds slightly better but has a much more restricted free monthly tier, google's and microsoft's has 1 million free characters per month which goes pretty far.
Like others are saying, it's slightly robotic but I've started to listen a ton by TTS and you definitely get used to it (you even start to hear inflection in it, which is cool). I use android smart audiobook app and you can control the sound levels, turning down the high pitch aspects also helps to make it easier to listen to for longer periods of time
For HN folks, there are some pretty reasonable research projects, especially by nvidia (glownet) which you can run yourself. They sound relatively similar but the training voices are much more restricted and not as good. If anyone knows of a github/etc with a nicer diy TTS I'd be interested. The best I've seen which is customizable is https://github.com/espnet/espnet but I had trouble getting it to work, then getting it to sound ok
(For anyone else going DIY I'll warn you that the failure modes for TTS is some unerring frankly creepy sounds. Google's TTS fails very well, even for strange words, and when it gets very confused it spells it out. Some of the research ones go into haunting unrelated syllables, sometimes repeating for 10s of seconds
Predictive AI layer for existing databases.
Deep recommender models using PyTorch.
Hummingbird compiles trained ML models into tensor computation for faster inference.Latest mention: I learned about Microsoft's Hummingbird library today. 1000x performance?? | dev.to | 2020-09-23
I took their sample code from Github and tweaked it to spit out times for each model's prediction, as well as increase the number of rows to 5 million. I used Google's Colab and selected GPU for my hardware accelerator. This gives an option to run code on GPU, not that all computations will happen on the GPU.
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.Latest mention: Apple’s New M1 Chip is a Machine Learning Beast | reddit.com/r/apple | 2020-12-25
And did you even know that Apple provides a CoreML conversion toolkit for converting models from PyTorch, TF, SKLearn and Keras to CoreML? You can comfortably train in your preferred tool and then convert the models to CoreML. (https://github.com/apple/coremltools). It currently supports a lot of conversions
An easier way to build neural search in the cloudLatest mention: Thank you Hacktoberfest! | dev.to | 2020-11-09
Basic Utilities for PyTorch Natural Language Processing (NLP)
torch-optimizer -- collection of optimizers for PytorchLatest mention: [R] AdasOptimizer Update: Cifar-100+MobileNetV2 Adas generalizes with Adas 15% better and 9x faster than Adam | reddit.com/r/MachineLearning | 2021-01-15
What are some of the best open-source Pytorch projects in Python? This list will help you: