distributed-computing

A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models

Super-Efficient RLHF Training of LLMs with Parameter Reallocation

[NeurIPS 2024] AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising

A front-end GUI for interacting with the AI Horde / Stable Diffusion distributed cluster

Chains stable-diffusion-webui instances together to facilitate faster image generation.

The default client software for volunteering to generate images for the crowdsourced AI-Horde

A Web Crawler based on LLMs implemented with Ray and Huggingface. The embeddings are saved into a vector database for fast clustering and retrieval. Use it for your RAG.

# Ollama<=>Ollama Inference Cluster

the small distributed language model toolkit; fine-tune state-of-the-art LLMs anywhere, rapidly

A comprehensive hands-on guide to building production-grade distributed applications with Ray - from distributed training and multimodal data processing to inference and reinforcement learning.

Batch LLM Inference with Ray Data LLM: From Simple to Advanced

A framework to orchestrate multiple AI agents, enabling them to collaborate efficiently through smart threading, dependency management, context sharing, and distributed execution via a built-in swarm system. Built on top of smolagents, it allows the creation of an AI dream team that can scale to tackle complex tasks.

Hotel-domain conversational assistant using Qwen2.5-7B-Instruct, focusing on practical, reproducible fine-tuning. It supports SFT + LoRA for a stable baseline, SFT + QLoRA for 7B model training with 4-bit quantization under limited GPU memory, and DPO to enhance responses via human preference pairs

Distributed model and API infrastructure for PyTorch and Hugging Face.