Best AI tools for< Predict Text >

Infinipilot.AI is an AI co-pilot application designed for macOS users to enhance productivity and streamline various tasks. It offers features such as autocomplete, style and grammar fixes, translation, developer utilities, and AI-driven question answering. The application prioritizes privacy by using local language models and provides accessibility features like text-to-speech and speech-to-text functionalities. Infinipilot.AI integrates with various AI models like OpenAI and Claude, ensuring efficient performance and continuous updates. The application also offers discounts for students and non-profit organizations, along with a 14-day money-back guarantee.

The GPT-2 Output Detector is an online tool that helps users identify whether a given text was generated by the GPT-2 language model. The tool is based on the RoBERTa implementation of Transformers, a popular natural language processing library. Users can enter text into the text box, and the tool will predict the probability that the text was generated by GPT-2. The results start to get reliable after around 50 tokens.

Walter AI is an advanced artificial intelligence tool designed to streamline business processes and enhance decision-making. It leverages machine learning algorithms to analyze data, generate insights, and provide predictive analytics. With its user-friendly interface, Walter AI empowers users to make data-driven decisions efficiently and effectively. Whether you are a small business owner or a corporate executive, Walter AI can help you unlock the power of your data and drive business growth.

SupportLogic is a Support Experience Management Platform that uses AI to help businesses improve their customer support operations. It offers a range of features, including sentiment analysis, backlog management, intelligent case routing, proactive alerts, swarming and collaboration, account health management, customer support analytics, text analytics, SLA/SLO management, quality monitoring and coaching, agent productivity, and translation. SupportLogic integrates with existing ticketing systems and apps, and can be implemented within 45 days.

Google DeepMind is an AI research company that aims to develop artificial intelligence technologies to benefit the world. They focus on creating next-generation AI systems to solve complex scientific and engineering challenges. Their models like Gemini, Veo, Imagen 3, SynthID, and AlphaFold are at the forefront of AI innovation. DeepMind also emphasizes responsibility, safety, education, and career opportunities in the field of AI.

ReadWrite is an award-winning tech website that provides trusted research and expert knowledge on the latest advancements in technology. Since 2003, ReadWrite has helped millions of people understand and solve tech problems, large and small. The website covers a wide range of tech topics, including AI, AR/VR, cryptocurrency, gaming, smartphones, gambling, wearables, and the web. ReadWrite's team of credentialed experts, trained researchers, and devoted community work together to create reliable, comprehensive, and engaging content that helps readers stay informed about the rapidly evolving tech landscape.

Future Tools is a website that collects and organizes AI tools. It provides a comprehensive list of AI tools categorized into various domains, including AI detection, aggregators, avatar chat, copywriting, finance, gaming, generative art, generative code, generative video, image improvement, image scanning, inspiration, marketing, motion capture, music, podcasting, productivity, prompt guides, research, self-improvement, social media, speech-to-text, text-to-speech, text-to-video, translation, video editing, and voice modulation. The website also offers a search bar to help users find specific tools based on their needs.

Supertools is a website that provides a curated directory of the best AI tools, organized and categorized in one spot. Users can browse through the latest AI tools, filter by category, and read detailed descriptions of each tool. Supertools also offers a newsletter that delivers the latest AI tools directly to users' inboxes.

Gooey.AI is a platform that provides access to a variety of AI models and tools, making it easy for users to build and deploy AI solutions. The platform offers a no-code interface, making it accessible to users of all skill levels. Gooey.AI also provides a community of users who share workflows and examples, making it easy to get started with AI development.

Stork is an AI App Directory & Marketplace that provides a comprehensive listing of over 9000 AI tools and agents. The platform allows users to search and discover AI tools based on their specific needs and preferences. Stork also offers a variety of resources and support to help users get the most out of AI technology.

Cohere is a leading provider of artificial intelligence (AI) tools and services. Our mission is to make AI accessible and useful to everyone, from individual developers to large enterprises. We offer a range of AI tools and services, including natural language processing, computer vision, and machine learning. Our tools are used by businesses of all sizes to improve customer service, automate tasks, and gain insights from data.

GptDemo.Net is a website that provides a directory of AI tools and resources. The website includes a search engine that allows users to find AI tools based on their needs. GptDemo.Net also provides news and updates on the latest AI developments.

AI-Hunter.io is a comprehensive AI tools directory that provides access to over 2000 AI tools across various categories. It offers a user-friendly interface for browsing and filtering tools based on categories, features, and pricing. The website also includes a blog section with AI-related news and articles, as well as a glossary of AI terms and a privacy policy.

This website is a personal blog of Viorel Spînu, who is a public speaker, backend developer, and AI enthusiast. The blog covers a wide range of topics related to AI, backend development, and other technical subjects. Spînu frequently writes about his experiences using AI tools and technologies, and he also shares his thoughts on the latest trends in the AI industry.

IAComunia is a directory of artificial intelligence tools. It provides a comprehensive list of AI tools organized into categories and subcategories. Users can discover, explore, and discuss the latest AI tools. IAComunia also has an active community where users can connect with other AI enthusiasts and share knowledge.

Pezzo is an open-source platform that enables developers to build, test, monitor, and ship AI features quickly and efficiently. It provides a range of powerful features to streamline the workflow, including prompt management, observability, troubleshooting, and collaboration tools. With Pezzo, teams can deliver impactful AI features in sync and optimize for cost and performance.

This website provides a weekly newsletter on generative AI, featuring new AI tools and deep dives into AI's impact on various industries. It aims to keep subscribers informed about the latest AI developments and inspire innovation.

Navalai.co is an AI-powered platform that offers advanced tools for data analysis, natural language processing, and machine learning. It provides users with the ability to extract insights from large datasets, automate repetitive tasks, and generate predictive models. The platform is designed to help businesses and researchers make data-driven decisions and improve efficiency in various domains.

Gaspard+Bruno is a premier AI consulting agency and platform dedicated to empowering businesses with high-end custom AI solutions. They offer sophisticated art direction and content production driven by technology, with a strong focus on exploration and technique. They value close and collaborative relationships with forward-thinking clients.

AI Monstaz is an innovative AI tool designed to assist users in various tasks using advanced artificial intelligence algorithms. The tool leverages machine learning and natural language processing to provide accurate and efficient solutions. With a user-friendly interface, AI Monstaz offers a seamless experience for users to interact with cutting-edge technology. Whether it's data analysis, language translation, or image recognition, AI Monstaz is your go-to tool for all AI-related needs.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

lmstudio.js is a pre-release alpha client SDK for LM Studio, allowing users to use local LLMs in JS/TS/Node. It is currently undergoing rapid development with breaking changes expected. Users can follow LM Studio's announcements on Twitter and Discord. The SDK provides API usage for loading models, predicting text, setting up the local LLM server, and more. It supports features like custom loading progress tracking, model unloading, structured output prediction, and cancellation of predictions. Users can interact with LM Studio through the CLI tool 'lms' and perform tasks like text completion, conversation, and getting prediction statistics.

Detoxify is a library that provides trained models and code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification. It includes models like 'original', 'unbiased', and 'multilingual' trained on different datasets to detect toxicity and minimize bias. The library aims to help in stopping harmful content online by interpreting visual content in context. Users can fine-tune the models on carefully constructed datasets for research purposes or to aid content moderators in flagging out harmful content quicker. The library is built to be user-friendly and straightforward to use.

Giskard is an open-source Python library that automatically detects performance, bias & security issues in AI applications. The library covers LLM-based applications such as RAG agents, all the way to traditional ML models for tabular data.

Tiny-Predictive-Text is a demonstration of predictive text without an LLM, using permy.link. It provides a detailed description of the tool, including its features, benefits, and how to use it. The tool is suitable for a variety of jobs, including content writers, editors, and researchers. It can be used to perform a variety of tasks, such as generating text, completing sentences, and correcting errors.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

Transformer Explainer is an interactive visualization tool to help users learn how Transformer-based models like GPT work. It allows users to experiment with text and observe how internal components of the Transformer predict next tokens in real time. The tool runs a live GPT-2 model in the browser, providing an educational experience on text-generative models.

This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

Next-Token Prediction is a language model tool that allows users to create high-quality predictions for the next word, phrase, or pixel based on a body of text. It can be used as an alternative to well-known decoder-only models like GPT and Mistral. The tool provides options for simple usage with built-in data bootstrap or advanced customization by providing training data or creating it from .txt files. It aims to simplify methodologies, provide autocomplete, autocorrect, spell checking, search/lookup functionalities, and create pixel and audio transformers for various prediction formats.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

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.

This tool is a machine learning AI used to predict the winners and under/overs of NBA games. It takes all team data from the 2007-08 season to the current season, matched with odds of those games, and uses a neural network to predict winning bets for today's games. The tool achieves ~69% accuracy on money lines and ~55% on under/overs. It outputs expected value for teams' money lines to provide better insight and the fraction of your bankroll to bet based on the Kelly Criterion. A popular, less risky approach is to bet 50% of the stake recommended by the Kelly Criterion.

CAPPr is a tool for text classification that does not require training or post-processing. It allows users to have their language models pick from a list of choices or compute the probability of a completion given a prompt. The tool aims to help users get more out of open source language models by simplifying the text classification process. CAPPr can be used with GGUF models, Hugging Face models, models from the OpenAI API, and for tasks like caching instructions, extracting final answers from step-by-step completions, and running predictions in batches with different sets of completions.

Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.

LlamaBot is a Pythonic bot interface to Large Language Models (LLMs), providing an easy way to experiment with LLMs in Jupyter notebooks and build Python apps utilizing LLMs. It supports all models available in LiteLLM. Users can access LLMs either through local models with Ollama or by using API providers like OpenAI and Mistral. LlamaBot offers different bot interfaces like SimpleBot, ChatBot, QueryBot, and ImageBot for various tasks such as rephrasing text, maintaining chat history, querying documents, and generating images. The tool also includes CLI demos showcasing its capabilities and supports contributions for new features and bug reports from the community.

llama.cpp is a C++ implementation of LLaMA, a large language model from Meta. It provides a command-line interface for inference and can be used for a variety of tasks, including text generation, translation, and question answering. llama.cpp is highly optimized for performance and can be run on a variety of hardware, including CPUs, GPUs, and TPUs.

Directrice de l'innovation chez KingLand, experte en IA, gestion de projets et R&D.

I predict DAU based on growth and retention.

Predict the future, opine on politics and controversial topics, and have GPT assess what is "true"

I predict future stock market prices. AI analyst. Your trading analysis assistant. Press H to bring up prompt hot key menu. Not financial advice.

Analyze Financial Statements step by step to Predict Earnings Direction

Predict fashion trends

AI expert in analyzing historical patterns to predict future events

Does Pool Performance of Elite Triathletes Predict Open-Water Performance?

A moot competition companion. & Trial Prep companion . Test and improve arguments- predict your opponent's reaction.

Personalized, analytical sports prediction AI.

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Predicts gender for first names using data

Our college entrance exam prediction app uses advanced algorithms and data analysis to provide accurate predictions for students preparing to take their college entrance exams.

Prédictif des tendances crypto à partir de la presse et des réseaux sociaux

Horoscopes--八字算命术预测你的健康、婚姻、事业、财富...

Analyzes and predicts the SSE 500 Index.

1620年代の主要な歴史的出来事を分析し未来の予測に役立てる。

A question ? Ask me for a prediction ... ( /help for help )

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Advanced AI for real-time predictive analysis using machine learning.