Projects sharing features with AdaBound

Vulpes: a Deep Belief Net written in F#, and using Alea.cuBase to access the GPU.

Fastai is a high-level deep learning library built on PyTorch that provides a unified interface for managing the entire machine learning lifecycle. It functions as a comprehensive training toolkit, abstracting hardware management and automating complex training loops to simplify the construction and execution of neural network models. The framework is distinguished by its notebook-centric development environment and a type-dispatching data pipeline that automatically applies transformations based on input data formats. It emphasizes transfer learning through discriminative layer-wise optimiza

A simplified framework and utilities for PyTorch

Netron is a visualizer for neural network and machine learning models. It provides a graphical interface that renders model architectures as interactive node-link diagrams, allowing users to inspect internal layers, tensors, and metadata. By performing static analysis, the tool enables the examination of model definitions without executing the underlying machine learning code. The software distinguishes itself through a schema-driven parsing engine that translates diverse proprietary model formats into a unified internal graph structure. This approach ensures interoperability, allowing users

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Keras-js is a JavaScript inference engine and browser-based machine learning framework designed to execute pre-trained Keras neural networks. It allows for client-side model inference in web browsers or Node.js environments without the requirement of a backend server. The library utilizes a WebGL tensor accelerator to map mathematical operations to the graphics processor for hardware acceleration. To maintain user interface responsiveness during heavy computations, it incorporates a web worker inference runtime that executes neural network processing in background threads. The system support

Keras Hyperopt: A very simple wrapper for convenient hyperparameter optimization

torch-optimizer -- collection of optimizers for Pytorch

Accelerate is a PyTorch distributed training library that abstracts the boilerplate required to run models across multiple GPUs, TPUs, and CPUs. It functions as a deep learning model scaler and distributed hardware orchestrator, allowing the same training script to run on different hardware backends without modifying the core logic. The project provides a distributed training command line interface for configuring compute environments and launching jobs across single or multi-node clusters. It includes a mixed precision training framework to implement FP16 and BF16 precision, reducing memory

Accelerated deep learning R&D

GPyTorch is a GPU-accelerated probabilistic framework and PyTorch library for implementing scalable Gaussian process models. It provides a system for Gaussian process modeling and uncertainty estimation, designed to perform efficient matrix operations on graphics hardware. The framework features a modular kernel system for constructing custom covariance functions and modeling complex data dependencies. It specifically integrates Gaussian processes with deep neural networks to create hybrid models for regression and classification. The system employs numerical linear algebra techniques, inclu

ANEE is an experimental dynamic inference wrapper for pretrained Transformer language models (currently GPT-2). Instead of always running all layers, ANEE exposes an energy_budget and performs early exit inside the model’s forward pass.

A helpful Chrome extension for WebGL development

Looker Gen

Console progress bar for Rust

This project is a developer knowledge base and a curated library of programming code snippets. It serves as a multi-language coding reference that provides short technical articles and reusable code samples to help developers implement common programming patterns. The resource functions as a multi-language syntax reference, allowing for the comparison of logic and functionality across different programming environments. It focuses on programming pattern learning and coding skill improvement through a collection of optimized patterns and best practices. The platform includes capabilities for

The autonomous, self-improving AI agent. Single Rust binary. Every channel.

Track and manage build artifacts from multiple programming languages.

Graphback - Out of the box GraphQL server and client

This project is a curated directory of command line applications and utilities designed to enhance developer productivity and streamline technical workflows. It serves as a comprehensive index of open-source software, categorizing tools that assist with system administration, development automation, and personal task management. The repository distinguishes itself by providing a structured collection of terminal-based software that spans diverse functional domains. It includes resources for managing infrastructure and cloud resources, performing code maintenance, and customizing terminal envi

All about erlang programming language powerd by community