Top Trending GitHub Projects This Week: Personalized AI, Video Diffusion & Fine-Tuning LLMs

Welcome to this week’s roundup of the top trending GitHub projects! Dive into the latest AI advancements, from building personalized knowledge bases to fine-tuning large language models and creating stunning video effects.

1. SuperMemory

SuperMemory is your personal AI-powered knowledge base. Easily save, organize, and retrieve information with the help of ChatGPT. Whether you’re a student, researcher, or professional, SuperMemory enhances knowledge retention and productivity.

Sponsored Project: Shakker AI

Before we move to our next project, let's introduce you to Shakker AI, a game-changer in digital creativity. With Shakker AI, you can turn your ideas into eye-catching images with just a few clicks. They offer the latest Stable Diffusion 3 and Hunyuan-DiT models, allowing you to create stunning images effortlessly.

Starting with Shakker AI is super easy and completely free. You get 200 tokens daily to experiment with different image generation features. Plus, from July 8th to the 31st, participate in their special event to fine-tune and release your own Hunyuan DiT models on Shakker AI and earn up to $230! Check out Shakker AI today.

2. SQL Eval

SQL Eval is a powerful tool designed to verify the accuracy of SQL queries generated by AI models. It ensures that your queries are efficient and error-free, making it indispensable for data scientists, developers, and database administrators.

3. AntonAI

AntonAI is a versatile AI chat platform optimized for Cloudflare Worker AI. It prioritizes privacy by keeping data local and offers features like natural language processing, multi-functionality, and image-to-text capabilities.

4. LLM-Interface

LLM-Interface simplifies interactions with a wide range of Large Language Models. With support for numerous providers, it offers a streamlined API that makes integrating LLM capabilities into your applications effortless.

5. Awesome Diffusion-v2v

This project is a comprehensive collection of resources on video-to-video (V2V) editing using AI diffusion models. It includes research papers and benchmark codes, making it an essential resource for developers and researchers in video editing.