CSVs of the Huggingface and LMSYS LLM leaderboards, along with the code to generate them in R.

a self-hosted webui for 30+ generative ai

Your offline AI pair programmer for VSCode on Windows.

project created with project idx from google, which consists of a chat that uses a hugging face model and an interface created with Nextjs and TailwindCSS

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

AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models

Automated Machine Learning on Kubernetes

Chitti is a retrieval-augmented-generation (RAG) application which utilizes a Mistral Large Language Model (LLM) for generation and a bge-m3 model developed by BAAI for retrieval. Chitti can help you answer questions about the IoT Summer Program, Projects in the program curriculum, Innovations of AIoT SMART Labs, Certification process and more!

Open source codebase powering the HuggingChat app

The platform for building AI from enterprise data

LightEval is a lightweight LLM evaluation suite that Hugging Face has been using internally with the recently released LLM data processing library datatrove and LLM training library nanotron.

Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.

A blazing fast inference solution for text embeddings models

This repo contains almost everything about Generative Ai

LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.

This is a RAG app that can run on multiple gpus simulteniously. I used Llama-Index framework for storing and retrieving documents, vLLM library for multiple gpu support.

A library for training and deploying machine learning models on Amazon SageMaker

A PyTorch-based Speech Toolkit

Distributed ML Training and Fine-Tuning on Kubernetes

⚗️ distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency.