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Community maintained fork of pdfminer - we fathom PDF
Enhanced ChatGPT Clone: Features OpenAI, Assistants API, Azure, Groq, GPT-4 Vision, Mistral, Bing, Anthropic, OpenRouter, Vertex AI, Gemini, AI model switching, message search, langchain, DALL-E-3,…
🌐 The Internet OS! Free, Open-Source, and Self-Hostable.
CV-CUDA™ is an open-source, GPU accelerated library for cloud-scale image processing and computer vision.
Distributed LLM inference for mobile, desktop and server.
《Hello 算法》:动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新,English version ongoing
A lightweight library for portable low-level GPU computation using WebGPU.
Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.
Video+code lecture on building nanoGPT from scratch
Automatically create Faiss knn indices with the most optimal similarity search parameters.
Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place!
The PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling
Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
A WebUI for Efficient Fine-Tuning of 100+ LLMs (ACL 2024)
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
The OpenAPI Specification Repository
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!
The official PyTorch implementation of Google's Gemma models
lightweight, standalone C++ inference engine for Google's Gemma models.
Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Machine Learning Engineering Open Book
Install and Run Python Applications in Isolated Environments