repollo's Stars
Significant-Gravitas/AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
trimstray/the-book-of-secret-knowledge
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
xtekky/gpt4free
The official gpt4free repository | various collection of powerful language models
Solido/awesome-flutter
An awesome list that curates the best Flutter libraries, tools, tutorials, articles and more.
BloopAI/bloop
bloop is a fast code search engine written in Rust.
geekyutao/Inpaint-Anything
Inpaint anything using Segment Anything and inpainting models.
togethercomputer/RedPajama-Data
The RedPajama-Data repository contains code for preparing large datasets for training large language models.
jtmuller5/The-HustleGPT-Challenge
Building Startups with an AI Co-Founder
Heinz-Loepmeier/nozzleboss
TIBHannover/GeoEstimation
This repository contains all necessary meta information, results and source files to reproduce the results in the publication Eric Müller-Budack, Kader Pustu-Iren, Ralph Ewerth: "Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification", In: European Conference on Computer Vision (ECCV), Munich, 2018.
ItsWajdy/modeler
A Python package to reconstruct 3D models from video
repollo/llm_data_parser
This is a proof-of-concept of using an LLM to find and extract meaningful data without parsing the html too much.
sergeybok/BaseBot
BaseBot is the open source Bot backend library compatible with the Friendly AI app that is available on App and Play Store.
kst179/fused-attention
Fast and low-memory attention layer written in CUDA
ohn0/youtube-livechat-scraper
grab youtube live chat data from existing VODs
HarshithK13/Attention-Based-Object-Classification-For-Drone-Imagery
The motivation is to use attention mechanisms that can help improve the accuracy and efficiency of object classification by focusing on the most relevant parts of the image rather than processing the entire image. The proposed attention-based CNN architecture was adopted and compared comprehensively with the existing networks like VGG16, etc.
rehadhawan/Attention-Span-Detection