Tags: #machine-learning

Unsloth Studio is a web UI that enables efficient local training and inference of open-source large language models and other AI models with significant VRAM and speed optimizations.

Ray is a unified framework for scaling AI and Python applications from a laptop to a cluster, simplifying complex ML workloads with a distributed runtime and specialized libraries.

A comprehensive library providing state-of-the-art pre-trained models for various machine learning tasks across text, vision, audio, and multimodal domains, facilitating both inference and training.

A state-of-the-art library for Parameter-Efficient Fine-Tuning (PEFT) of large pretrained models, drastically reducing computational and storage costs.

Provides sample code, notebooks, and resources for building and managing generative AI workflows on Google Cloud using Vertex AI and Gemini.

An open-source AI engineering platform for debugging, evaluating, monitoring, and optimizing production-quality AI applications, including agents, LLMs, and ML models.

A unified and efficient framework for fine-tuning over 100 large language models (LLMs) and vision-language models (VLMs) with both CLI and Web UI.

A production-ready, pre-trained time series foundation model (TimeGPT) for accurate forecasting and anomaly detection across various domains with minimal code.

A comprehensive repository housing open-source code and datasets officially released by Google Research.

A human-centric Python framework for building, managing, and deploying real-life AI/ML systems from rapid prototyping to reliable production.

An industrial-strength Python library for advanced Natural Language Processing, offering state-of-the-art models and a production-ready training system.

An AI developer platform for tracking, visualizing, and managing machine learning models from experimentation to production.

A universal viewer for neural network, deep learning, and machine learning models, supporting a wide array of formats.

DVC (Data Version Control) is a command-line tool and VS Code extension for managing data, models, and ML experiments, enabling reproducible machine learning projects.

An open standard and format for machine learning models, enabling interoperability across different AI frameworks and hardware.

A comprehensive, free online course from Hugging Face designed to teach the fundamentals and advanced techniques of building AI agents.

A comprehensive repository offering over 50 tutorials and implementations for building Generative AI agents, from basic conversational bots to complex multi-agent systems.

A repository showcasing various advanced Retrieval-Augmented Generation (RAG) techniques through detailed notebook tutorials.

A comprehensive open-source library providing AI agents with the skills to autonomously conduct the entire AI research lifecycle, from ideation to paper writing.

A standardized, scalable, multi-framework platform for deploying generative and predictive AI models on Kubernetes.

An open-source, cloud-native vector database enabling semantic search at scale by combining vector similarity with structured filtering and AI capabilities.

A high-performance, massive-scale vector database and search engine designed for next-generation AI applications.

An open-source, container-native workflow engine for Kubernetes, designed to orchestrate parallel jobs and complex multi-step tasks.

An open-source, multi-type data labeling and annotation tool with a simple UI and standardized output, designed to prepare and improve data for machine learning models.

A meticulously curated list of battle-tested, production-proven open-source AI projects, models, tools, and infrastructure.

An open-source platform for building, deploying, and managing end-to-end machine learning workflows on Kubernetes.

A comprehensive curated list of open-source libraries for deploying, monitoring, versioning, and scaling machine learning models in production.

A collection of Jupyter notebooks demonstrating how to build, train, and deploy machine learning models using Amazon SageMaker and its new Python SDK, SageMaker-Core.

A comprehensive MLOps platform for managing, orchestrating, and scaling the machine learning lifecycle with reproducibility and automation.

An open-source feature store for AI/ML that streamlines the management and serving of features for model training and online inference.

A Kubernetes-native platform for scalable distributed AI model training and LLM fine-tuning across various frameworks.

A comprehensive and categorized collection of awesome MLOps tools and resources, designed to help practitioners navigate the complex MLOps ecosystem.

Build machine learning models from natural language prompts using an AI-powered multi-agent system.

A comprehensive educational platform teaching developers how to design, develop, deploy, and iterate on production-grade machine learning applications.

A versatile framework designed to train and optimize AI agents from any framework with minimal code changes, leveraging advanced algorithms like Reinforcement Learning.

Deep Lake is an AI data runtime and database optimized for deep learning, offering serverless multimodal data storage, scalable retrieval, and training capabilities.

A low-code, declarative framework for building and deploying custom large language models (LLMs) and other deep neural networks with ease and efficiency.

A comprehensive, curated list of modern Generative Artificial Intelligence projects, services, and learning resources.

A 12-week, 24-lesson curriculum from Microsoft to learn Artificial Intelligence for beginners, including practical lessons, quizzes, and labs.

A comprehensive and curated list of the best LLMOps tools, resources, and frameworks for developers working with large language models and other AI models.

A comprehensive toolkit providing best practices, examples, and state-of-the-art algorithms to assist in prototyping, experimenting with, and operationalizing recommendation systems.

A lightweight library providing one-line dataloaders and efficient pre-processing tools for a vast hub of AI datasets, supporting various ML frameworks.

A comprehensive collection of Jupyter Notebooks and sample applications designed to help developers master Pinecone vector databases and common AI patterns through hands-on practice.

A Python library for representing, transmitting, storing, and retrieving multimodal data, designed for AI applications.

A comprehensive repository offering practical implementations and evaluation guidance for advanced and agentic Retrieval-Augmented Generation (RAG) techniques.

A high-performance, scalable JAX-based open-source library for training large language models on Google Cloud TPUs and GPUs.

A user-friendly, versatile fine-tuning kit for image, video, and audio diffusion models, emphasizing simplicity and cutting-edge features.

A streamlined tool to accelerate the fine-tuning of popular multimodal models like Florence-2, PaliGemma 2, and Qwen2.5-VL.

A collection of guides and code for efficiently fine-tuning large language models using PEFT (LoRA) and Hugging Face transformers.

Enables efficient fine-tuning of LLMs, Vision, Audio, and OCR models on Apple Silicon Macs with an Unsloth-compatible API.

A comprehensive collection of PyTorch implementations for over 60 deep learning papers, featuring side-by-side annotated notes for enhanced understanding.

Provides Google Colab notebooks for easily deploying and running Stable Diffusion WebUI, enabling AI-powered image generation and training without local hardware.

A comprehensive GUI and script collection for training LoRA and Dreambooth models for Stable Diffusion, built upon kohya-ss's sd-scripts.

A comprehensive open-source textbook and code repository dedicated to Reinforcement Learning from Human Feedback (RLHF) and post-training language models.

A continually updated, curated list of essential resources for Reinforcement Learning with Human Feedback (RLHF), encompassing research papers, codebases, and datasets.

A modular open-source framework for training constrained value-aligned Large Language Models (LLMs) using Safe Reinforcement Learning from Human Feedback (RLHF).

A comprehensive collection of recipes and code for training various reward models crucial for Reinforcement Learning from Human Feedback (RLHF) in large language models.

Docta is an advanced data-centric AI platform that detects and rectifies issues in various data types to improve model performance.

FinGPT democratizes access to large language models tailored for finance, offering cost-effective and rapidly adaptable solutions to overcome the limitations of proprietary financial AI.

Extends ComfyUI with advanced custom nodes for the LTX-2 video generation model, enabling powerful text-to-video and image-to-video workflows.

A comprehensive and continuously updated collection and categorization of research papers on diffusion models.

A fast, minimal PyTorch port of DALL·E Mini for efficient text-to-image generation.

A collection of pre-trained, end-to-end text-to-speech models designed for simplicity, speed, and natural-sounding speech across multiple languages.

An easy-to-use open-source toolkit built on PaddlePaddle, offering state-of-the-art models for diverse speech and audio tasks like ASR, TTS, translation, and speaker verification.

A user-friendly, high-quality AI-powered tool for transforming voices with a focus on performance and customization.

A comprehensive repository offering structured learning paths, practical projects, and career preparation resources for Generative AI and Machine Learning.

MTEB is a comprehensive benchmark and evaluation framework designed to assess the performance of text embedding models and retrieval systems across a wide range of tasks.

A comprehensive Python library for multi-modal anomaly detection, featuring 60+ algorithms and agentic AI capabilities for scalable, expert-level investigations.

A comprehensive toolkit for computing CLIP embeddings and building scalable semantic search and retrieval systems for multimodal data.

An open-source MLOps and AI orchestration platform for building, managing, and automating continuous machine learning and generative AI applications across their entire lifecycle.

PostgresML integrates machine learning and AI capabilities, including LLMs and vector search, directly into PostgreSQL, leveraging GPUs for high-performance in-database inference.

A comprehensive, curated collection of free resources for learning AI, Machine Learning, LLMs, and AI Engineering from scratch.

StyleTTS 2 is a cutting-edge text-to-speech model achieving human-level speech synthesis through style diffusion and adversarial training with large speech language models.

A deep learning library for advanced, high-quality, and efficient Text-to-Speech (TTS) synthesis, supporting multiple languages and models.

A highly efficient command-line tool to download, resize, and package large sets of image URLs into machine learning datasets.

A comprehensive repository offering expert-level tutorials, guides, and courses on Generative AI, focusing on Stable Diffusion, SDXL, LoRA, DreamBooth, and related technologies.

Create dynamic and visually captivating videos by smoothly morphing between different text prompts using Stable Diffusion.

Provides fast, cloud-based (Google Colab) notebooks for Stable Diffusion, ComfyUI, AUTOMATIC1111, and DreamBooth.

A comprehensive, open-source repository of Data Science learning resources and tools for real-world problem-solving.

A weekly curated repository highlighting the most impactful machine learning and AI research papers.

A comprehensive Python toolkit for machine learning tasks specifically tailored for time series analysis.

A meticulously curated list of battle-tested, production-proven open-source AI projects, models, tools, and infrastructure.

A comprehensive, AI-native learning platform to master AI engineering from foundational math to autonomous agent swarms, building and shipping real tools.

An open-source, low-code AutoML platform for Python, offering a sklearn-native engine and a React-based control plane for end-to-end machine learning workflows.

A free 9-week online course from DataTalks.Club, designed to teach the fundamentals of MLOps, from experimentation to deployment and monitoring.

A meticulously curated collection of links to free courses and resources covering various Artificial Intelligence (AI) topics, suitable for all learning levels.

An open-source web application that leverages AI to generate personalized avatars from user-provided images.

A repository of common solutions and tools developed by Google Cloud's Professional Services team to address various challenges on Google Cloud Platform.