Global

Run frontier MoE models on hardware you already own — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦

Heretic is a tool that removes censorship (aka "safety alignment") from transformer-based language models without expensive post-training. It combines an advanced implementation of directional ablation, also known as "abliteration" (Arditi et al.

NOTE] > Based on this course, I co-wrote the LLM Engineer's Handbook, a hands-on book that covers an end-to-end LLM application from design to deployment. The LLM course will always stay free, but you can support my work by purchasing this book.

PyTorch implementation of VisionHOPE, a visual backbone based on self-referential nested learning (SRNL).

Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification.

8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. cpp and MLX.

Implementing LLM architectures from scratch in PyTorch

> Kronos is the first open-source foundation model for financial candlesticks (K-lines), > trained on data from over 45 global exchanges.

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).

A high-throughput and memory-efficient inference and serving engine for LLMs

Most people learn ML frameworks by importing them. We built ours by hand, then made it hit harder.

Explore the world of Artificial Intelligence (AI) with our 12-week, 24-lesson curriculum! It includes practical lessons, quizzes, and labs. The curriculum is beginner-friendly and covers tools like TensorFlow and PyTorch, as well as ethics in AI

This repository provides a research-grade, unsupervised anomaly detection framework for microservice logs, combining multi-modal embeddings, graph attention networks, hybrid ensembles with GMM thresholding, streaming simulation, and explainability (SHAP + gradients).

2 is a state-of-the-art large 3D generative model (4B parameters) designed for high-fidelity image-to-3D generation.

12 · NVIDIA GPU with BF16 support and 24 GB VRAM. YuE2 produces 48 kHz stereo audio without quantization. Model files download from Hugging Face on first use.

To download the model weights manually, use the following command:

预览地址为 ，简体中文位于根目录，英文与繁體中文分别位于 en/ 和 zh-tw/。生成文件位于 build/，详细说明见网站构建与发布。

We advise to run all examples through Google Colab for the easiest setup. Google Colab allows you to use a T4 GPU with 16GB of VRAM for free. All examples were mainly built and tested using Google Colab, so it should be the most stable platform.

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

SGLang is a high-performance serving framework for large language models and multimodal models.

md and local files. yaml only adds optional UI metadata (display name, description, default prompt) for the ChatGPT/Codex skills UI, per OpenAI's skill spec — it does not limit the skill to OpenAI agents.

faster-whisper is a reimplementation of OpenAI's Whisper model using CTranslate2, which is a fast inference engine for Transformer models.

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.

Update Nov 2025 nanoGPT has a new and improved cousin called nanochat. It is very likely you meant to use/find nanochat instead. nanoGPT (this repo) is now very old and deprecated but I will leave it up for posterity.

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

FreeToken brings datacenter-scale model serving to your desktop. Run massive models locally, fast and efficiently.

IMPORTANT] > For SGLang server, please read SGLang-Omni README. > > For vLLM Omni server, please read vLLM-Omni Fish Speech S2 Pro Recipe and the User Guide.

OBLITERATUS is the most advanced open-source toolkit for understanding and removing refusal behaviors from large language models — and every single run makes it smarter.

The raw source assets are available on the Hugging Face Hub (collected under UniMate): Mixamo-Animations-Characters, Objaverse-XL-Rigged-Animated and Truebones-ZOO-Annotations (prompts, metadata and renders only).

cpp. The rest of the code is part of the ggml machine learning library.