Popular GitHub Repositories for Styled Components

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

NVIDIA? TensorRT? is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

Typescript/React Library for AI Chat??

AI generated UI components

A library of reinforcement learning components and agents

UI for your AI. Open Source Tailwind components tailored for your GPT, generative AI, and LLM projects.

[ICLR2025 Spotlight] SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

Core building blocks for AI apps. High-quality, accessible, and customizable components for AI interfaces.

Build and iterate on your UI 10x faster with AI - right from your own IDE ??

? Landing page UI components for React & Next.js, built on top of TailwindCSS

? Lobe UI - an open-source UI component library for building AIGC web apps

Generate React and Tailwind components using AI

Perception and AI components for autonomous mobile robotics.

A simple and well styled PPO implementation. Based on my Medium series: https://medium.com/@eyyu/coding-ppo-from-scratch-with-pytorch-part-1-4-613dfc1b14c8.

? A PyTorch library of curated Transformer models and their composable components

? Components Library for Quickly Building LLM Chat Interfaces.

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.

Flexible components pairing ? Transformers with :zap: Pytorch Lightning