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A high-throughput and memory-efficient inference and serving engine for LLMs
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
llama3 implementation one matrix multiplication at a time
fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
GPT based autonomous agent that does online comprehensive research on any given topic
VILA - a multi-image visual language model with training, inference and evaluation recipe, deployable from cloud to edge (Jetson Orin and laptops)
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory
Deep Reinforcement Learning: Zero to Hero!
Python packaging and dependency management made easy
Tesseract Open Source OCR Engine (main repository)
⛓️ Langflow is a visual framework for building multi-agent and RAG applications. It's open-source, Python-powered, fully customizable, model and vector store agnostic.
Jan is an open source alternative to ChatGPT that runs 100% offline on your computer. Multiple engine support (llama.cpp, TensorRT-LLM)
OCR, layout analysis, reading order, line detection in 90+ languages
Open Source Metering and Usage Based Billing API ⭐️ Consumption tracking, Subscription management, Pricing iterations, Payment orchestration & Revenue analytics
🆙 Upscayl - #1 Free and Open Source AI Image Upscaler for Linux, MacOS and Windows.
Tools and documentation for Win32 app isolation
8 Lessons, Kick-start Your Cybersecurity Learning.
DSPy: The framework for programming—not prompting—foundation models
ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
A curated list of resources for Document Understanding (DU) topic
An Open Source text-to-speech system built by inverting Whisper.