Popular GitHub Repositories for Less

Finetune Llama 3.3, DeepSeek-R1 & Reasoning LLMs 2x faster with 70% less memory! ?

Type less, code more: Cody is an AI code assistant that uses advanced search and codebase context to help you write and fix code.

Type less, code more: Cody is an AI code assistant that uses advanced search and codebase context to help you write and fix code.

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute

Deploy a ML inference service on a budget in less than 10 lines of code.

HyperGen - Optimized inference and fine-tuning framework for diffusion (image & video) models. Up to 3x faster & 80% less VRAM.

Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)

Helping Ethical Hackers use LLMs in 50 Lines of Code or less..

[CVPR 2024] Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Models, a no lighting baked texture generative model

A personal news aggregator to pull information from multi-sources + LLM (ChatGPT/Gemini/Ollama via LangChain) to help us reading efficiently with less noises, the sources including: Tweets, RSS, YouTube, Web Articles, Reddit, and personal Journal notes.

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

A framework-less approach to robust agent development.

PyTorch Implementation of CVPR 2025 "Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection". The first multi-class UAD model that can compete with single-class SOTAs

OpenAI GPT3/3.5 and GPT4 ChatGPT API Client Library for Go, simple, less dependencies, and well-tested

Shinkai is a two click install App that allows you to create Local AI agents in 5 minutes or less using a simple UI. Supports: MCPs, Remote and Local AI, Crypto and Payments.

User can set up destination for any agent to navigate on Google Map and learn the best route for the agent based on its current condition and the traffic. Our result is 10% less energy consumption than the route provided by Google map

LLM-based text extraction from unstructured data like PDFs, Words and HTMLs. Transform and cluster the text into your desired format. Less information loss, more interpretation, and faster R&D!

[ ICCV 2021 Oral ] Our method can estimate camera poses and neural radiance fields jointly when the cameras are initialized at random poses in complex scenarios (outside-in scenes, even with less texture or intense noise )

Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"