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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
scikit-learn: machine learning in Python
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
A toolkit for developing and comparing reinforcement learning algorithms.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
The fundamental package for scientific computing with Python.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
The official Python library for the OpenAI API
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Graph Neural Network Library for PyTorch
PyScript is an open source platform for Python in the browser. Try PyScript: https://pyscript.com Examples: https://tinyurl.com/pyscript-examples Community: https://discord.gg/HxvBtukrg2
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
🚀 Level up your GitHub profile readme with customizable cards including LOC statistics!
A computer algebra system written in pure Python
Convert Machine Learning Code Between Frameworks
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
📝 A text file containing 479k English words for all your dictionary/word-based projects e.g: auto-completion / autosuggestion
Minimal and clean examples of machine learning algorithms implementations
A python library for user-friendly forecasting and anomaly detection on time series.