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5 GB of RAM. Weights stream from SSD; a trained router predicts loads a step ahead. Mac, iPhone, Android, Windows supported

This repository contains the code for developing, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book Build a Large Language Model (From Scratch).

青简 Qingjian：用 Rust 写的拼音输入法，候选词旁多一条正在学的语言的译词

LIST OF ALL MY JAILBREAKS

> Prefer to Clone Locally? > > This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout: > > Bash / macOS / Linux: >

Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics.

AI System Design - Learn how to design AI systems built on LLMs, RAG, and AI Agents step by step.

5. The text models cover 150 languages and follow translation instructions such as terminology, formatting, and content-preservation requirements. The family extends this foundation to speech, syllable-controlled translation, and full-document translation.

GPT4Free (g4f) is a community-driven project that aggregates multiple accessible providers and interfaces to make working with modern LLMs and media-generation models easier and more flexible.

A course on neural networks that starts all the way at the basics. The course is a series of YouTube videos where we code and train neural networks together. The Jupyter notebooks we build in the videos are then captured here inside the lectures directory.

The AI Toolkit for TypeScript. js, the AI SDK is a free open-source library for building AI-powered applications and agents

📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, DeepSeek, Perplexity, Gemini, Gemma, Llama, Grok, and more.

0 release of lm-evaluation-harness is available !

Kimi K3 is an open-weight, native multimodal agentic model and our most capable model to date. 8T-parameter model built on Kimi Delta Attention (KDA) and Attention Residuals (AttnRes), with native vision capabilities and a 1-million-token context window.

app — the end-signal probe, public pages, and the live steered-model lab.

We are releasing MiniCPM5-2B, the second model in the MiniCPM5 series, following MiniCPM5-1B. It is a dense 2B Transformer that scales up the same training recipe, built for on-device, local deployment, and resource-constrained scenarios, reaching 2B-class open-source SOTA.

A low-latency, fully modular voice-agent pipeline: VAD -> STT -> LLM -> TTS, exposed through the core OpenAI Realtime GA event set over WebSocket and WebRTC. Every component is swappable. cpp server on your own hardware for a fully local, fully open stack.

I implemented a transformer model from scratch using PyTorch, based on the paper Attention is All You Need. You can use my scripts to train your own billion or million parameter LLM using a single GPU.

Finally, to build SWE-bench from source, follow these steps:

mini-AGI - is a continual learning byte-level language model that assembles its own architecture, trains from scratch on a single 8 GB VRAM GPU, and keeps learning from everything it reads.

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

A PyTorch re-implementation of GPT, both training and inference. minGPT tries to be small, clean, interpretable and educational, as most of the currently available GPT model implementations can a bit sprawling. py).

WebLLM is a high-performance in-browser LLM inference engine that brings language model inference directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU.

Minimal, clean code for the (byte-level) Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings.

Thank you for developing with Llama models. 1 release, we’ve consolidated GitHub repos and added some additional repos as we’ve expanded Llama’s functionality into being an e2e Llama Stack.

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

An open source implementation of CLIP.

This code implements multi-layer Recurrent Neural Network (RNN, LSTM, and GRU) for training/sampling from character-level language models.

MLC LLM is a machine learning compiler and high-performance deployment engine for large language models. The mission of this project is to enable everyone to develop, optimize, and deploy AI models natively on everyone's platforms.

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows