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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.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
Rich is a Python library for rich text and beautiful formatting in the terminal.
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Streamlit — A faster way to build and share data apps.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
PyTorch Tutorial for Deep Learning Researchers
You like pytorch? You like micrograd? You love tinygrad! ❤️
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Turn (almost) any Python command line program into a full GUI application with one line
Typer, build great CLIs. Easy to code. Based on Python type hints.
pix2tex: Using a ViT to convert images of equations into LaTeX code.
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
DALL·E Mini - Generate images from a text prompt
Image augmentation for machine learning experiments.
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
🐍 Geometric Computer Vision Library for Spatial AI
Python bindings for FFmpeg - with complex filtering support
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
A faster pytorch implementation of faster r-cnn