ONNX Interface for Framework Integration is a cross-platform API for loading and executing ONNX graphs on optimized backends. This package contains facebook extensions and is used by PyTorch.

This package is a stand-alone implementation of several NumPy dtype extensions used in machine learning libraries, including:

• bfloat16: an alternative to the standard float16 format

• float8_*: several experimental 8-bit floating point representations including:

  • float8_e4m3b11fnuz

  • float8_e4m3fn

  • float8_e4m3fnuz

  • float8_e5m2

  • float8_e5m2fnuz

• int4 and uint4: low precision integer types.

This package enables you to deserialize Lua torch-serialized objects from Python.

PyNNDescent provides a Python implementation of Nearest Neighbor Descent for k-neighbor-graph construction and approximate nearest neighbor search.

This is a package for hassle-free computation of shareable, comparable, and reproducible BLEU, chrF, and TER scores for natural language processing.

This package provides a GStreamer plugin that wraps Kaldi's SingleUtteranceNnet2Decoder. It requires iVector-adapted DNN acoustic models. The iVectors are adapted to the current audio stream automatically.

NNPACK is an acceleration package for neural network computations. NNPACK aims to provide high-performance implementations of convnet layers for multi-core CPUs.

NNPACK is not intended to be directly used by machine learning researchers; instead it provides low-level performance primitives leveraged in leading deep learning frameworks, such as PyTorch, Caffe2, MXNet, tiny-dnn, Caffe, Torch, and Darknet.

This package provides a speech recognition toolkit based on kaldi. It supports more than 20 languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish. The program works offline, even on lightweight devices. Portable per-language models are about 50Mb each, and there are much bigger and precise models available.

Vosk API provides a streaming API allowing to use it on-the-fly and bindings for different programming languages. It allows quick reconfiguration of vocabulary for better accuracy, and supports speaker identification beside simple speech recognition.

This package provides an implementation of today’s most used tokenizers, with a focus on performance and versatility.

ggml is a ML library written in C and C++ with a focus on transformer inference, similar to ML libraries such as PyTorch and TensorFlow.

The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.

XNNPACK is a highly optimized library of floating-point neural network inference operators for ARM, WebAssembly, and x86 platforms. XNNPACK is not intended for direct use by deep learning practitioners and researchers; instead it provides low-level performance primitives for accelerating high-level machine learning frameworks, such as TensorFlow Lite, TensorFlow.js, PyTorch, and MediaPipe.

Dlib is a modern C++ toolkit containing machine learning algorithms and tools. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments.

Apache TVM is a compiler stack for deep learning systems. It is designed to close the gap between the productivity-focused deep learning frameworks, and the performance- and efficiency-focused hardware backends. TVM works with deep learning frameworks to provide end to end compilation to different backends

ONNX is a format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.

Apache Burr makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple Python building blocks. Apache Burr works well for any application that uses LLMs, and can integrate with any of your favorite frameworks. Burr includes a UI that can track/monitor/trace your system in real time, along with pluggable persisters (e.g. for memory) to save and load application state.

This package provides simple access speech to text for using in Linux without being tied to a desktop environment, using the vosk-api. The user configuration lets you manipulate text using Python string operations. It has zero overhead, as this relies on manual activation and there are no background processes. Dictation is accessed manually with nerd-dictation begin and nerd-dictation end commands.

DMLC-Core is the backbone library to support all DMLC projects, offers the bricks to build efficient and scalable distributed machine learning libraries.

DMLC-Core is the backbone library to support all DMLC projects, offers the bricks to build efficient and scalable distributed machine learning libraries.

This package includes a variety of tools used to analyze persistence diagrams. It currently houses implementations of

• Persistence images

• Persistence landscapes

• Bottleneck distance

• Modified Gromov–Hausdorff distance

• Sliced Wasserstein kernel

• Heat kernel

• Diagram plotting

cleanlab automatically finds and fixes errors in any ML dataset. This data-centric AI package facilitates machine learning with messy, real-world data by providing clean labels during training.

Scikit-learn provides simple and efficient tools for data mining and data analysis.

Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which may include real-valued, discrete, and conditional dimensions.

QNNPACK is a library for low-precision neural network inference. It contains the implementation of common neural network operators on quantized 8-bit tensors.