#pytorch

End-to-end ML toolkit automating the complete workflow — data profiling, preprocessing, feature engineering, model selection, training, validation, explainability, drift monitoring, fairness checks, and interactive HTML reporting. Includes a full CLI for zero-code ML pipelines. Python 3.10+.

The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.

A multi-backend graph learning library.

Profile PyTorch models for FLOPs and parameters, helping to evaluate computational efficiency and memory usage.

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

Fast kernel library for Diffusion inference with multiple compute backends.

Fault tolerance for PyTorch (HSDP, LocalSGD, DiLoCo, Streaming DiLoCo)

NeLux: High-performance video processing for Python, powered by FFmpeg and PyTorch. Ultra-fast video decoding directly to tensors.

Graph-based weather forecasting models. Originally, PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)

Next-gen AI-native tensor-network-based quantum software framework

🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

PyTorch Implementation of Google Research's MetNet and MetNet-2

Scaleout Edge: Sovereign Edge AI orchestration and Federated Learning

Training-free KV cache compression via E8 lattice VQ. 2-bit KV that preserves retrieval (30/30 NIAH vs TurboQuant 0/30). Calibration-free, 9 architectures validated.

A convenient CLI to streamline LiteRT related development workflows, including converting, quantizing, compiling, managing, running, benchmarking and visualizing LiteRT (TFLite) models on various hardwares (CPU / GPU / NPU) across platforms (desktop, mobile or cloud).

State-of-the-art 2D and 3D Face Analysis Project

A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.

An open-source deep learning framework for data mining of protein-protein interfaces or single-residue variants.

JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).

JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).

depyf is a tool to help you understand and adapt to PyTorch compiler torch.compile.

Benchmarking framework for protein representation learning. Includes a large number of pre-training and downstream task datasets, models and training/task utilities. (ICLR 2024)

🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

PyTorch Extension Library of Optimized Scatter Operations

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

CnSTD: 基于 PyTorch/MXNet 的 中文/英文 场景文字检测（Scene Text Detection）、数学公式检测（Mathematical Formula Detection, MFD）、篇章分析（Layout Analysis）的Python3 包

Stable Diffusion web UI

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

Config-driven PyTorch training framework: assemble nets, data, losses and trainers from YAML