dbt-transformation-patterns — detailed patterns and worked examples captures reusable agent playbook guidance for research & evaluation. Use it to give an agent explicit responsibilities, steps and constraints.

A curated list of recent diffusion models for video generation, editing, restoration, understanding, nerf, etc. Use it to navigate the topic and choose relevant methods, papers or tools.

logo]: https://github.com/rohan-paul/rohan-paul/blob/master/assets/png. Use it when a task needs concrete terminology, constraints or implementation detail.

Official PyTorch implementation for Extreme Compression of Large Language Models via Additive Quantization. Use it to navigate the topic and choose relevant methods, papers or tools.

Zhen Xing, Qijun Feng, Haoran Chen, Qi Dai, Han Hu, Hang Xu, Zuxuan Wu, Yu-Gang Jiang. Use it to navigate the topic and choose relevant methods, papers or tools.

VideoCrafter is an open-source video generation and editing toolbox for crafting video content. It currently includes the Text2Video and Image2Video models:. Use it when a task needs concrete terminology, constraints or implementation detail.

MedAlpaca expands upon both Stanford Alpaca and AlpacaLoRA to offer an advanced suite of large language models specifically fine-tuned for medical question-answering and dialogue applications. Our primary objective is to deliver an array of open-source language models, paving the way for seamless development of medical chatbot solutions.

Implementation of Band Split Roformer , SOTA Attention network for music source separation out of ByteDance AI Labs. They beat the previous first place by a large margin.

Implementation of SoundStorm , Efficient Parallel Audio Generation from Google Deepmind, in Pytorch. They basically applied MaskGiT to the residual vector quantized codes from Soundstream .

SimpleTuner is geared towards simplicity, with a focus on making the code easily understood. This codebase serves as a shared academic exercise, and contributions are welcome.

Get structured, fully typed, and validated JSON outputs from OpenAI and Anthropic models. Under the hood, zod-gpt uses functions to coerce the model to always respond as function calls.

A powerful local RAG (Retrieval Augmented Generation) application that lets you chat with your PDF documents using Ollama and LangChain. This project includes multiple interfaces: a modern Next.js web app, a Streamlit interface, and Jupyter notebooks for experimentation.

Prompt Decorators extend the functionality of large language models by allowing structured, modular control over reasoning, style, and behavior. Each decorator enforces specific response rules, enabling users to declaratively modify how the model thinks and writes — without retraining.

For embeddings, please see examples/embeddings/index.html WebGPU support is introduced via PR #215. Upon updating to V3.1, WebGPU will be enabled automatically.

⚠️ Warning: Not Actively Maintained This repository is no longer actively maintained. For a more up-to-date alternative, please visit the LitGPT project: https://github.com/Lightning-AI/litgpt , which serves as the successor to this repository.

In a nutshell, we aim to generate polyphonic music of multiple tracks (instruments). The proposed models are able to generate music either from scratch, or by accompanying a track given a priori by the user.

An open-source visual environment for battle-testing prompts to LLMs. ChainForge is a data flow prompt engineering environment for analyzing and evaluating LLM responses.

We also introduce a diffusion-based value model that reduces variance and improves stability during optimization. Based on TraceRL, we derive a series of diffusion language models, TraDo, which achieve state-of-the-art performance on math and coding reasoning tasks.

RouteLLM is a framework for serving and evaluating LLM routers. [Blog ] [Paper ] Our core features include: From PyPI From source Let's walkthrough replacing an existing OpenAI client to route queries between LLMs instead of using only a single model.

MASFactory is a graph-centric framework for orchestrating Multi-Agent Systems with Vibe Graphing: Start from intent, generate a graph design, preview and refine it in a visual environment, compile it into an executable workflow, and trace node states, messages, and shared state at runtime. Turn natural-language intent into a structural design, then iteratively converge to an executable, reusable workflow.