Best AI tools for< Train On Data >

Botsonic is an AI chatbot application that offers custom AI chatbots for websites. It provides AI-powered automation solutions for various industries, enabling businesses to enhance customer engagement, support, sales, and more. Botsonic uses AI Copilots trained on data to deliver authentic customer experiences in multiple languages across different channels. The platform allows users to easily create, customize, and integrate AI chatbots into their websites, providing instant support and personalized interactions.

EmbedAI is a platform that enables users to create custom AI chatbots powered by ChatGPT. Users can train the chatbot on their own data and embed it on their website. The platform allows for customization of the chatbot's appearance and supports multiple languages. EmbedAI aims to provide efficient management of information and automated responses to user queries.

Chunky is an AI chatbot builder that allows users to create human-like chatbots effortlessly. With Chunky, you can automate customer support, train your bot on your own data, and integrate it seamlessly into your website. The platform offers a user-friendly interface, fast and personal support, and a generous free forever plan. Chunky is powered by the ChatGPT API and Embeddings provided by OpenAI, supporting close to 95 languages for both training data and bot responses.

SQLAI.ai is a professional SQL multi-tool that leverages AI technology to generate, fix, explain, and optimize SQL queries and databases. It enables users to interact with SQL using everyday language, effortlessly train AI to understand database schemas, and benefit from AI-driven recommendations for query optimization. The platform caters to a wide range of users, from beginners to experts, by simplifying SQL tasks and providing valuable insights for database management. With features like generating SQL data, data analytics, and real-time data insights, SQLAI.ai revolutionizes the way users interact with databases, making SQL tasks simpler, more efficient, and accessible to all.

Chatflot is an AI chatbot application that helps businesses automate up to 95% of customer queries. It allows users to create customized AI chatbots based on the ChatGPT language model, enabling them to provide on-demand information to customers through their website. Chatflot is suitable for various industries and offers features like training the chatbot on specific data, optimizing customer interactions, and integrating seamlessly with different CMS platforms. The application aims to enhance customer service, boost sales, and streamline support processes by providing personalized assistance and relevant information to users.

ChatCube is an AI-powered chatbot maker that allows users to create chatbots for their websites without coding. It uses advanced AI technology to train chatbots on any document or website within 60 seconds. ChatCube offers a range of features, including a user-friendly visual editor, lightning-fast integration, fine-tuning on specific data sources, data encryption and security, and customizable chatbots. By leveraging the power of AI, ChatCube helps businesses improve customer support efficiency and reduce support ticket reductions by up to 28%.

ChatFast is a platform that allows businesses to create custom GPT chatbots using their own data. These chatbots can be used to answer customer questions, capture leads, and schedule appointments. ChatFast is easy to use and requires no coding. It is trusted by thousands of businesses and provides a range of powerful features, including the ability to train chatbots on multiple data sources, revise responses, capture leads, and create smart forms.

SQLAI.ai is a powerful SQL multi-tool that utilizes AI to generate, fix, explain, and optimize SQL queries and databases. It empowers users to effortlessly create complex SQL queries using everyday language, optimize queries for better performance, fix syntax errors with ease, and gain a deeper understanding of SQL queries through AI-powered explanations. Additionally, SQLAI.ai enables users to train AI on their database schema, ensuring unparalleled accuracy in AI-generated queries and optimizations.

Vize.ai is a custom image recognition API provided by Ximilar, a leading company in Visual AI and Search. The tool offers powerful artificial intelligence capabilities with high accuracy using deep learning algorithms. It allows users to easily set up and implement cutting-edge vision automation without any development costs. Vize.ai enables users to train custom neural networks to recognize specific images and provides a scalable solution with continuous improvements in machine learning algorithms. The tool features an intuitive interface that requires no machine learning or coding knowledge, making it accessible for a wide range of users across industries.

Quivr is an open-source chat-powered second brain application that transforms private and enterprise knowledge into a personal AI assistant. It continuously learns and improves at every interaction, offering AI-powered workplace search synced with user data. Quivr allows users to connect with their favorite tools, databases, and applications, and configure their 'second brain' to train on their company's unique context for improved search relevance and knowledge discovery.

Mirage is a custom AI platform that builds custom LLMs to accelerate productivity. It is backed by Sequoia and offers a variety of features, including the ability to create custom AI models, train models on your own data, and deploy models to the cloud or on-premises.

Lexy is an AI chatbot application designed to enhance customer service on websites. It integrates with Notion pages to provide instant, human-like answers to customer queries. Lexy can be set up in just 5 minutes, prioritizes data security, and can be trained on specific Notion pages. The application is free to create the first bot and send 30 messages per month, with options to upgrade for more power.

ColdIQ is an AI-powered sales prospecting tool that helps B2B companies with revenue above $100k/month to build outbound systems that sell for them. The tool offers end-to-end cold outreach campaign setup and management, email infrastructure setup and warmup, audience research and targeting, data scraping and enrichment, campaigns optimization, sending automation, sales systems implementation, training on tools best practices, sales tools recommendations, free gap analysis, sales consulting, and copywriting frameworks. ColdIQ leverages AI to tailor messaging to each prospect, automate outreach, and flood calendars with opportunities.

Netomi is an AI-powered conversational AI platform that revolutionizes customer experience by providing proactive and automated customer care across various channels. It offers industry-leading enterprise-ready AI solutions, including sanctioned generative AI, goal-driven AI, and federated knowledge access. Netomi enables businesses to quickly respond to customer needs, increase resolution rates, and reduce support costs. The platform integrates seamlessly with existing systems, providing real-time omnichannel intelligence and security-first architecture for data privacy and security.

360Learning is a comprehensive learning platform that leverages AI and collaborative features to transform in-house experts into L&D collaborators. It enables organizations to upskill quickly and continuously within their own environment. The platform offers a range of features to facilitate collaborative learning, course creation, compliance training, employee onboarding, sales enablement, and frontline staff training. With a focus on data protection and security, 360Learning is trusted by over 2,300 customers for its innovative approach to corporate learning.

Chatling is a no-code AI chatbot builder that empowers businesses to create custom chatbots without the need for coding expertise. With Chatling, businesses can train chatbots on their own data, customize them to match their brand, and add them to their website in minutes. Chatling's chatbots can answer customer queries instantly, resolve issues accurately, and provide 24/7 support, leading to increased customer satisfaction, reduced customer support workload, and cost savings.

HumanEcho is an AI-powered platform offering Custom ChatGPT and Digital Human services for websites. It provides advanced AI technologies to enhance customer experience by offering AI chatbots and lifelike digital personas that can interact with users in real-time. The platform allows users to train the AI on their data, upload documents or website URLs, and embed chatbots easily. With features like next-level customer engagement, easy data integration, accurate answers, 24/7 customer support, and support for 80+ languages, HumanEcho aims to revolutionize customer engagement and support services.

Surge AI is a data labeling platform that provides human-generated data for training and evaluating large language models (LLMs). It offers a global workforce of annotators who can label data in over 40 languages. Surge AI's platform is designed to be easy to use and integrates with popular machine learning tools and frameworks. The company's customers include leading AI companies, research labs, and startups.

Browse AI is an AI tool that offers the easiest way to extract and monitor data from any website without the need for coding. Users can train a robot in just 2 minutes to extract specific data in spreadsheet format or monitor data on a schedule. With over 7,000 integrations, Browse AI allows users to scrape structured data, run multiple robots simultaneously, emulate user interactions, handle pagination, and more. Trusted by over 370,000 individuals and teams, Browse AI is a powerful tool for data extraction and monitoring tasks.

Chaindesk is a no-code platform that allows businesses to train custom ChatGPT chatbots on their own data. With Chaindesk, businesses can automate customer support, lead generation, and more. Chaindesk's chatbots are secure, precise, and can be deployed on a variety of platforms, including websites, WhatsApp, and Slack.

Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.

DataDreamer is a powerful open-source Python library designed for prompting, synthetic data generation, and training workflows. It is simple, efficient, and research-grade, allowing users to create prompting workflows, generate synthetic datasets, and train models with ease. The library is built for researchers, by researchers, focusing on correctness, best practices, and reproducibility. It offers features like aggressive caching, resumability, support for bleeding-edge techniques, and easy sharing of datasets and models. DataDreamer enables users to run multi-step prompting workflows, generate synthetic datasets for various tasks, and train models by aligning, fine-tuning, instruction-tuning, and distilling them using existing or synthetic data.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

qlora-pipe is a pipeline parallel training script designed for efficiently training large language models that cannot fit on one GPU. It supports QLoRA, LoRA, and full fine-tuning, with efficient model loading and the ability to load any dataset that Axolotl can handle. The script allows for raw text training, resuming training from a checkpoint, logging metrics to Tensorboard, specifying a separate evaluation dataset, training on multiple datasets simultaneously, and supports various models like Llama, Mistral, Mixtral, Qwen-1.5, and Cohere (Command R). It handles pipeline- and data-parallelism using Deepspeed, enabling users to set the number of GPUs, pipeline stages, and gradient accumulation steps for optimal utilization.

LitGPT is a command-line tool designed to easily finetune, pretrain, evaluate, and deploy 20+ LLMs **on your own data**. It features highly-optimized training recipes for the world's most powerful open-source large-language-models (LLMs).

ALMA (Advanced Language Model-based Translator) is a many-to-many LLM-based translation model that utilizes a two-step fine-tuning process on monolingual and parallel data to achieve strong translation performance. ALMA-R builds upon ALMA models with LoRA fine-tuning and Contrastive Preference Optimization (CPO) for even better performance, surpassing GPT-4 and WMT winners. The repository provides ALMA and ALMA-R models, datasets, environment setup, evaluation scripts, training guides, and data information for users to leverage these models for translation tasks.

DeepPavlov is an open-source conversational AI library built on PyTorch. It is designed for the development of production-ready chatbots and complex conversational systems, as well as for research in the area of NLP and dialog systems. The library offers a wide range of models for tasks such as Named Entity Recognition, Intent/Sentence Classification, Question Answering, Sentence Similarity/Ranking, Syntactic Parsing, and more. DeepPavlov also provides embeddings like BERT, ELMo, and FastText for various languages, along with AutoML capabilities and integrations with REST API, Socket API, and Amazon AWS.

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.

BlindChat is a confidential and verifiable Conversational AI tool that ensures user prompts remain private from the AI provider. It leverages privacy-enhancing technology called enclaves with the core solution, BlindLlama. BlindChat Local variant operates entirely in the user's browser, ensuring data never leaves the device. The tool provides cryptographic guarantees that user data is protected and not accessible to AI providers.

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.

The Intel® Geti™ SDK is a python package that enables teams to rapidly develop AI models by easing the complexities of model development and enhancing collaboration between teams. It provides tools to interact with an Intel® Geti™ server via the REST API, allowing for project creation, downloading, uploading, deploying for local inference with OpenVINO, setting project and model configuration, launching and monitoring training jobs, and media upload and prediction. The SDK also includes tutorial-style Jupyter notebooks demonstrating its usage.

WebWhiz is an open-source tool that allows users to train ChatGPT on website data to build AI chatbots for customer queries. It offers easy integration, data-specific responses, regular data updates, no-code builder, chatbot customization, fine-tuning, and offline messaging. Users can create and train chatbots in a few simple steps by entering their website URL, automatically fetching and preparing training data, training ChatGPT, and embedding the chatbot on their website. WebWhiz can crawl websites monthly, collect text data and metadata, and process text data using tokens. Users can train custom data, but bringing custom open AI keys is not yet supported. The tool has no limitations on context size but may limit the number of pages based on the chosen plan. WebWhiz SDK is available on NPM, CDNs, and GitHub, and users can self-host it using Docker or manual setup involving MongoDB, Redis, Node, Python, and environment variables setup. For any issues, users can contact [email protected].

Vanna is an open-source Python framework for SQL generation and related functionality. It uses Retrieval-Augmented Generation (RAG) to train a model on your data, which can then be used to ask questions and get back SQL queries. Vanna is designed to be portable across different LLMs and vector databases, and it supports any SQL database. It is also secure and private, as your database contents are never sent to the LLM or the vector database.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

Instruct NER is a solution for complex Named Entity Recognition tasks, including Nested NER, based on modern Large Language Models (LLMs). It provides tools for dataset creation, training, automatic metric calculation, inference, error analysis, and model implementation. Users can create instructions for LLM, build dictionaries with labels, and generate model input templates. The tool supports various entity types and datasets, such as RuDReC, NEREL-BIO, CoNLL-2003, and MultiCoNER II. It offers training scripts for LLMs and metric calculation functions. Instruct NER models like Llama, Mistral, T5, and RWKV are implemented, with HuggingFace models available for adaptation and merging.

Uni-MoE is a MoE-based unified multimodal model that can handle diverse modalities including audio, speech, image, text, and video. The project focuses on scaling Unified Multimodal LLMs with a Mixture of Experts framework. It offers enhanced functionality for training across multiple nodes and GPUs, as well as parallel processing at both the expert and modality levels. The model architecture involves three training stages: building connectors for multimodal understanding, developing modality-specific experts, and incorporating multiple trained experts into LLMs using the LoRA technique on mixed multimodal data. The tool provides instructions for installation, weights organization, inference, training, and evaluation on various datasets.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

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