Instant voice cloning by MIT and MyShell.

A Cheat Sheet 📜 to revise Python syntax. Particularly useful for solving Data Structure and Algorithmic problems with Python.

Official implementation of VQMIVC: One-shot (any-to-any) Voice Conversion @ Interspeech 2021 + Online playing demo!

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

An unofficial Python wrapper for OpenAI's ChatGPT API

A timeline of the latest AI models for audio generation, starting in 2023!

A collection of useful python data structures, tricks, and must-knows for coding interviews

🔊 A comprehensive list of open-source datasets for voice and sound computing (95+ datasets).

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

Knowledge Distillation: CVPR2020 Oral, Revisiting Knowledge Distillation via Label Smoothing Regularization

Design patterns implemented in Java

🔥 Machine Learning Notebooks

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

BERT-related papers

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Reference implementation of the Transformer architecture optimized for Apple Neural Engine (ANE)

A collection of resources and papers on Diffusion Models

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

PyTorch Tutorial for Deep Learning Researchers

funny little random job title generator written in JavaScript / Python

UrbanSound classification using Convolutional Recurrent Networks in PyTorch

A free audio dataset of gujarati spoken digits. Think MNIST for audio.

Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"

A list of multi-task learning papers and projects.

Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.

Jupyter notebooks for the Natural Language Processing with Transformers book

🔍 AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your da…

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)