Package list
sci-ml / FBGEMM : Facebook GEneral Matrix Multiplication
sci-ml / FP16 : conversion to/from half-precision floating point formats
sci-ml / NNPACK : acceleration package for neural network computations
sci-ml / XNNPACK : library of floating-point neural network inference operators
sci-ml / accelerate : Run your *raw* PyTorch training script on any kind of device
sci-ml / caffe2 : A deep learning framework
sci-ml / cudnn-frontend : A c++ wrapper for the cudnn backend API
sci-ml / datasets : Access and share datasets for Audio, Computer Vision, and NLP tasks
sci-ml / evaluate : makes evaluating, comparing models and reporting their performance easier
sci-ml / fastai : The fastai deep learning library
sci-ml / fastcore : Python supercharged for the fastai library
sci-ml / fastdownload : Easily download, verify, and extract archives
sci-ml / fastprogress : Simple and flexible progress bar for Jupyter Notebook and console
sci-ml / foxi : ONNXIFI with Facebook Extension
sci-ml / gemmlowp : Low-precision matrix multiplication
sci-ml / gloo : library of floating-point neural network inference operators
sci-ml / huggingface_hub : a client library to interact with the Hugging Face Hub
sci-ml / ideep : Intel® Optimization for Chainer
sci-ml / jiwer : Evaluate an automatic speech recognition system
sci-ml / kineto : part of the PyTorch Profiler
sci-ml / oneDNN : oneAPI Deep Neural Network Library
sci-ml / onnx : Open Neural Network Exchange (ONNX)
sci-ml / pysentencepiece : Text tokenizer for Neural Network-based text generation
sci-ml / pytorch : Tensors and Dynamic neural networks in Python
sci-ml / safetensors : Simple, safe way to store and distribute tensors
sci-ml / sentencepiece : Text tokenizer for Neural Network-based text generation
sci-ml / seqeval : Python framework for sequence labeling evaluation
sci-ml / tensorpipe : provides a tensor-aware channel
sci-ml / tokenizers : Implementation of today's most used tokenizers
sci-ml / torchvision : Datasets, transforms and models to specific to computer vision
sci-ml / transformers : State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow