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🎃Tools & Framework
Datasets, Transforms and Models specific to Computer Vision
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Collection of Pytorch lightning tutorial form as rich scripts automatically transformed to ipython notebooks.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Using queues, tqdm-multiprocess supports multiple worker processes, each with multiple tqdm progress bars, displaying them cleanly through the main process. It offers similar functionality for pyth…
Code snippets created for the PyTorch discussion board
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
State-of-the-art 2D and 3D Face Analysis Project
Machine learning metrics for distributed, scalable PyTorch applications.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
LibAUC: A Deep Learning Library for X-Risk Optimization
Benchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)
(CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers
This is a collection of our NAS and Vision Transformer work.
Python code for "Probabilistic Machine learning" book by Kevin Murphy
(N=1,2,3)-dimensional unfold (im2col) and fold (col2im) in PyTorch
A playbook for systematically maximizing the performance of deep learning models.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Optimized primitives for collective multi-GPU communication
Samples for CUDA Developers which demonstrates features in CUDA Toolkit
A library for efficient similarity search and clustering of dense vectors.
Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
This is a pytorch implementation of k-means clustering algorithm
Fast and memory-efficient exact attention
Profiling and inspecting memory in pytorch