Yeyo's starred repositories

ollama

Get up and running with Llama 3, Mistral, Gemma, and other large language models.

tesseract

Tesseract Open Source OCR Engine (main repository)

Language:C++License:Apache-2.0Stargazers:59227Issues:1683Issues:2613

dayjs

⏰ Day.js 2kB immutable date-time library alternative to Moment.js with the same modern API

Language:JavaScriptLicense:MITStargazers:46128Issues:282Issues:1618

hurl

Hurl, run and test HTTP requests with plain text.

Language:RustLicense:Apache-2.0Stargazers:12137Issues:46Issues:608

novel

Notion-style WYSIWYG editor with AI-powered autocompletion.

Language:TypeScriptLicense:Apache-2.0Stargazers:11585Issues:40Issues:209

khoj

Your AI second brain. Get answers to your questions, whether they be online or in your own notes. Use online AI models (e.g gpt4) or private, local LLMs (e.g llama3). Self-host locally or use our cloud instance. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp.

Language:PythonLicense:AGPL-3.0Stargazers:11544Issues:65Issues:403

OpenLLM

Run any open-source LLMs, such as Llama 2, Mistral, as OpenAI compatible API endpoint in the cloud.

Language:PythonLicense:Apache-2.0Stargazers:9157Issues:54Issues:253

no-more-secrets

A command line tool that recreates the famous data decryption effect seen in the 1992 movie Sneakers.

Language:CLicense:GPL-3.0Stargazers:7499Issues:129Issues:50

arwes

Futuristic Sci-Fi UI Web Framework.

Language:TypeScriptLicense:MITStargazers:7021Issues:138Issues:114

vaul

An unstyled drawer component for React.

Language:TypeScriptLicense:MITStargazers:5199Issues:11Issues:216

arrow-js

Reactivity without the framework

Language:TypeScriptLicense:MITStargazers:2306Issues:29Issues:54

zap

blazingly fast backends in zig

aurelia

Aurelia 2, a standards-based, front-end framework designed for high-performing, ambitious applications.

Language:TypeScriptLicense:MITStargazers:1355Issues:56Issues:542
Language:C++License:GPL-2.0Stargazers:1145Issues:62Issues:12

perfect_dark

work in progress port of n64decomp/perfect_dark to modern platforms

daktilo

Turn your keyboard into a typewriter! 📇

Language:RustLicense:Apache-2.0Stargazers:988Issues:7Issues:29

ra

A Raft implementation for Erlang and Elixir that strives to be efficient and make it easier to use multiple Raft clusters in a single system.

Language:ErlangLicense:NOASSERTIONStargazers:791Issues:45Issues:118

next-ls

The language server for Elixir that just works. Ready for early adopters!

Language:ElixirLicense:MITStargazers:639Issues:7Issues:165

live_view_native

A framework for building native applications with Phoenix LiveView

Language:ElixirLicense:MITStargazers:420Issues:16Issues:70

llama-tokenizer-js

JS tokenizer for LLaMA 1 and 2

Language:JavaScriptLicense:MITStargazers:316Issues:3Issues:11

mummy

An HTTP and WebSocket server for Nim that returns to the ancient ways of threads.

Language:NimLicense:MITStargazers:260Issues:8Issues:35

lemmy-ansible

A docker deploy for ansible

Language:JinjaLicense:AGPL-3.0Stargazers:251Issues:10Issues:112

finetuned-qlora-falcon7b-medical

Finetuning of Falcon-7B LLM using QLoRA on Mental Health Conversational Dataset

Language:Jupyter NotebookLicense:MITStargazers:221Issues:4Issues:2

xlsxir

Xlsx parser for the Elixir language.

Language:ElixirLicense:MITStargazers:210Issues:13Issues:53

kanta

User-friendly translations manager for Elixir/Phoenix projects.

Language:ElixirLicense:MITStargazers:166Issues:7Issues:16

tokenizers

Elixir bindings for 🤗 Tokenizers

Language:ElixirLicense:Apache-2.0Stargazers:90Issues:11Issues:8

awesome-onprem

A list of companies that use on-premise infrastructure heavily

ecto_commons

Ecto common validators for Date, Time, URLs, Emails, PostalCodes, Phone Numbers, Luhn checks, etc.

Language:ElixirLicense:MITStargazers:49Issues:4Issues:1

date_time_parser

Parse strings into DateTime, NaiveDateTime, Date, or Time https://hexdocs.pm/date_time_parser

Language:ElixirLicense:MITStargazers:26Issues:3Issues:6

aws-document-classifier-and-splitter

In this repository you will find an aws-sample that will create a AWS Comprehend classification model from documents. It will then use that classification model to split documents.

Language:PythonLicense:MIT-0Stargazers:15Issues:2Issues:3