Best AI tools for< Tune Database Systems >

Keebo is an AI tool designed for Snowflake optimization, offering automated query, cost, and tuning optimization. It is the only fully-automated Snowflake optimizer that dynamically adjusts to save customers 25% and more. Keebo's patented technology, based on cutting-edge research, optimizes warehouse size, clustering, and memory without impacting performance. It learns and adjusts to workload changes in real-time, setting up in just 30 minutes and delivering savings within 24 hours. The tool uses telemetry metadata for optimizations, providing full visibility and adjustability for complex scenarios and schedules.

Song Identifier is an AI tool that helps users find a song by entering words from the lyrics. The tool utilizes AI technology to match the input lyrics with a vast database of songs, providing users with accurate results. Created with love by Pablo, Song Identifier aims to assist users in identifying songs stuck in their heads quickly and effortlessly.

Defog.ai provides fine-tuned AI models for enterprise SQL. It helps businesses speed up data analyses in SQL, Python, and R with AI assistants and agents tailored for their business - without sharing their data. Defog.ai's key features include the ability to ask questions of data in natural language, get results when needed, integrate with any SQL database or data warehouse, automatically visualize data as tables and charts, and fine-tune on your metadata to give results you can trust.

Binaural Beats Factory is an AI-powered online self-hypnosis, subliminal, and affirmation audio generator that helps users achieve their goals by creating personalized audio tracks. The tool uses binaural beats, subliminal suggestions, and positive affirmations to target the subconscious mind and create positive changes in thoughts, feelings, and behaviors. Binaural Beats Factory offers a range of features, including a user-friendly online application, a vast database of single tone frequencies, background music, and subliminal affirmations, and the ability to fine-tune settings live while listening. The tool also includes a public library of self-hypnosis, subliminal, and affirmation audio tracks created by other users or the Binaural Beats Factory team.

Infrabase.ai is a directory of AI infrastructure products that helps users discover and explore a wide range of tools for building world-class AI products. The platform offers a comprehensive directory of products in categories such as Vector databases, Prompt engineering, Observability & Analytics, Inference APIs, Frameworks & Stacks, Fine-tuning, Audio, and Agents. Users can find tools for tasks like data storage, model development, performance monitoring, and more, making it a valuable resource for AI projects.

Tune AI is an enterprise Gen AI stack that offers custom models to build competitive advantage. It provides a range of features such as accelerating coding, content creation, indexing patent documents, data audit, automatic speech recognition, and more. The application leverages generative AI to help users solve real-world problems and create custom models on top of industry-leading open source models. With enterprise-grade security and flexible infrastructure, Tune AI caters to developers and enterprises looking to harness the power of AI.

Tune Chat is a chat application that utilizes open-source Large Language Models (LLMs) to provide users with a conversational and informative experience. It is designed to understand and respond to a wide range of user queries, offering assistance with various tasks and engaging in natural language conversations.

re:tune is a no-code AI app solution that provides everything you need to transform your business with AI, from custom chatbots to autonomous agents. With re:tune, you can build chatbots for any use case, connect any data source, and integrate with all your favorite tools and platforms. re:tune is the missing platform to build your AI apps.

Fine-Tune AI is a tool that allows users to generate fine-tune data sets using prompts. This can be useful for a variety of tasks, such as improving the accuracy of machine learning models or creating new training data for AI applications.

FaceTune.ai is an AI-powered photo editing tool that allows users to enhance their selfies and portraits with various features such as skin smoothing, teeth whitening, and blemish removal. The application uses advanced algorithms to automatically detect facial features and make precise adjustments, resulting in professional-looking photos. With an intuitive interface and real-time editing capabilities, FaceTune.ai is a popular choice for individuals looking to improve their selfies before sharing them on social media.

HeyPhoto is an AI photo editor online that utilizes artificial intelligence to enhance and manipulate facial features in photos. Users can tune selfies and group photos by changing gaze direction, skin tone, age, hair style, and other facial attributes. The tool offers a range of features such as face anonymization, gender transformation, age modification, emotion tweaking, skin tone adjustment, and more. HeyPhoto is user-friendly and requires no special skills, making it accessible for individuals looking to edit their photos effortlessly.

Prompteasy.ai is an AI tool that allows users to fine-tune AI models in less than 5 minutes. It simplifies the process of training AI models on user data, making it as easy as having a conversation. Users can fully customize GPT by fine-tuning it to meet their specific needs. The tool offers data-driven customization, interactive AI coaching, and seamless model enhancement, providing users with a competitive edge and simplifying AI integration into their workflows.

ReplyInbox is a Gmail Chrome extension that revolutionizes email management by harnessing the power of AI. It automates email replies based on your product or service knowledge base, saving you time and effort. Simply select the text you want to respond to, click generate, and let ReplyInbox craft a personalized and high-quality reply. You can also share website links and other documentation with ReplyInbox's AI to facilitate even more accurate and informative responses.

IBM Watsonx is an enterprise studio for AI builders. It provides a platform to train, validate, tune, and deploy AI models quickly and efficiently. With Watsonx, users can access a library of pre-trained AI models, build their own models, and deploy them to the cloud or on-premises. Watsonx also offers a range of tools and services to help users manage and monitor their AI models.

FinetuneDB is an AI fine-tuning platform that allows users to easily create and manage datasets to fine-tune LLMs, evaluate outputs, and iterate on production data. It integrates with open-source and proprietary foundation models, and provides a collaborative editor for building datasets. FinetuneDB also offers a variety of features for evaluating model performance, including human and AI feedback, automated evaluations, and model metrics tracking.

Imajinn AI is a cutting-edge visualization tool that utilizes the latest in AI technology to reimagine photos and images into stunning works of art. The platform offers a suite of AI-powered products and tools, including personalized children's books, couples portraits, product visualizer, sneaker generator, and a WordPress plugin. Users can create memorable gifts, products, and experiences with Imajinn's AI-powered tools, making it easy to transform ordinary photos into extraordinary creations. Imajinn also provides users with the ability to train custom AI models, generate concept images, and download raw AI model checkpoints for further use in their applications.

Gretel.ai is a synthetic data platform designed for Generative AI applications. It allows users to generate artificial datasets with the same characteristics as real data, enabling the improvement of AI models without compromising privacy. The platform offers various features such as building synthetic data pipelines, rule-based data transformation, measuring data quality, and customizing language models. Gretel.ai is suitable for industries like finance, healthcare, and the public sector, providing a secure and efficient solution for data generation and model enhancement.

Predibase is a platform for fine-tuning and serving Large Language Models (LLMs). It provides a cost-effective and efficient way to train and deploy LLMs for a variety of tasks, including classification, information extraction, customer sentiment analysis, customer support, code generation, and named entity recognition. Predibase is built on proven open-source technology, including LoRAX, Ludwig, and Horovod.

PromptLeo is a prompt engineering platform designed to empower organizations in effectively applying Generative AI. It offers a simple interface for prompt engineers to create, test, and change prompts, integrating Generative AI into daily workflows without the need to store prompts in text files. With features like prompt templates, feedback loop & iterations, access to multiple models, and a dedicated prompt engineering library, PromptLeo aims to streamline prompt management and versioning, enhance prompt performance tracking, and facilitate collaboration among team members.

Labelbox is a data factory platform that empowers AI teams to manage data labeling, train models, and create better data with internet scale RLHF platform. It offers an all-in-one solution comprising tooling and services powered by a global community of domain experts. Labelbox operates a global data labeling infrastructure and operations for AI workloads, providing expert human network for data labeling in various domains. The platform also includes AI-assisted alignment for maximum efficiency, data curation, model training, and labeling services. Customers achieve breakthroughs with high-quality data through Labelbox.

The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.

LLM4DB is a repository focused on the intersection of Large Language Models (LLMs) and Database technologies. It covers various aspects such as data processing, data analysis, database optimization, and data management for LLMs. The repository includes research papers, tools, and techniques related to leveraging LLMs for tasks like data cleaning, entity matching, schema matching, data discovery, NL2SQL, data exploration, data visualization, knob tuning, query optimization, and database diagnosis.

MindsDB is a platform for customizing AI from enterprise data. You can create, serve, and fine-tune models in real-time from your database, vector store, and application data. MindsDB "enhances" SQL syntax with AI capabilities to make it accessible for developers worldwide. With MindsDB’s nearly 200 integrations, any developer can create AI customized for their purpose, faster and more securely. Their AI systems will constantly improve themselves — using companies’ own data, in real-time.

Hailo TAPPAS is a set of full application examples that implement pipeline elements and pre-trained AI tasks. It demonstrates Hailo's system integration scenarios on predefined systems, aiming to accelerate time to market, simplify integration with Hailo's runtime SW stack, and provide a starting point for customers to fine-tune their applications. The tool supports both Hailo-15 and Hailo-8, offering various example applications optimized for different common hosts. TAPPAS includes pipelines for single network, two network, and multi-stream processing, as well as high-resolution processing via tiling. It also provides example use case pipelines like License Plate Recognition and Multi-Person Multi-Camera Tracking. The tool is regularly updated with new features, bug fixes, and platform support.

Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

LightRAG is a repository hosting the code for LightRAG, a system that supports seamless integration of custom knowledge graphs, Oracle Database 23ai, Neo4J for storage, and multiple file types. It includes features like entity deletion, batch insert, incremental insert, and graph visualization. LightRAG provides an API server implementation for RESTful API access to RAG operations, allowing users to interact with it through HTTP requests. The repository also includes evaluation scripts, code for reproducing results, and a comprehensive code structure.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

LLMInterviewQuestions is a repository containing over 100+ interview questions for Large Language Models (LLM) used by top companies like Google, NVIDIA, Meta, Microsoft, and Fortune 500 companies. The questions cover various topics related to LLMs, including prompt engineering, retrieval augmented generation, chunking, embedding models, internal working of vector databases, advanced search algorithms, language models internal working, supervised fine-tuning of LLM, preference alignment, evaluation of LLM system, hallucination control techniques, deployment of LLM, agent-based system, prompt hacking, and miscellaneous topics. The questions are organized into 15 categories to facilitate learning and preparation.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. It enables a data & learning flywheel for LLMs by unifying inference, observability, optimization, and experimentation. The platform includes a high-performance model gateway, structured schema-based inference, observability, experimentation, and data warehouse for analytics. TensorZero Recipes optimize prompts and models, and the platform supports experimentation features and GitOps orchestration for deployment.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

The 'END TO END GENERATIVE AI PROJECTS' repository is a collection of awesome industry projects utilizing Large Language Models (LLM) for various tasks such as chat applications with PDFs, image to speech generation, video transcribing and summarizing, resume tracking, text to SQL conversion, invoice extraction, medical chatbot, financial stock analysis, and more. The projects showcase the deployment of LLM models like Google Gemini Pro, HuggingFace Models, OpenAI GPT, and technologies such as Langchain, Streamlit, LLaMA2, LLaMAindex, and more. The repository aims to provide end-to-end solutions for different AI applications.

安達孝一さんがSE時代に蓄積してきた、Oracle RDBMSのナレッジやノウハウ等 (Oracle 7/8.1.6/8.1.7/9iR1/9iR2/10gR1/10gR2/11gR2/12c/SQLチューニング) について、ご質問頂けます。また、対話内容を基に、ChatGPT(GPT-4)向けの、汎用的な質問文例も作成できます。

SQL Server consultant for DBAs and organizations.

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An assistant to help you understand transfer learning better

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ギターについてなんでもお答えします

Expert in ML model optimization and tuning!

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大型语言模型的学习和训练指导专家

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