Best AI tools for< Dry Clothes >

Speechify is the #1 rated AI text to speech app in its category with over 250,000 5 star reviews. It is available as a Chrome extension, iOS app, Android app, Microsoft Edge Add-on, and web app. Speechify can convert any text into natural-sounding AI voice in over 50 languages and accents. It can also read aloud any PDF, doc, or web page. Speechify is used by students, professionals, readers, and those who struggle to read. It can help with reading comprehension, focus, and retention. Speechify is also a great tool for people with disabilities such as dyslexia, ADHD, and dry eyes.

ACE Studio is an AI Vocal Workstation that allows users to generate vocals from various professional AI vocalists by typing MIDI and lyrics. It simplifies the production of lead vocals, harmonies, backing vocals, and choirs. The platform features a next-generation AI Singing Synthesis Engine that aims to deliver natural and expressive vocal performances. Users can access over 41 AI pro-singers in English, Chinese, and Japanese for music production. ACE Studio offers tools for editing and controlling vocal emotions, converting dry vocals into MIDI clips, blending voices, and customizing AI voice models.

PlayWord is a tool designed to supercharge web test automation experience with AI. It provides core features such as enabling browser operations and validations using natural language inputs, as well as monitoring interface to record and dry-run test steps. PlayWord supports multiple AI services including Anthropic, Google, and OpenAI, allowing users to select the appropriate provider based on their requirements. The tool also offers features like assertion handling, frame handling, custom variables, test recordings, and an Observer module to track user interactions on web pages. With PlayWord, users can interact with web pages using natural language commands, reducing the need to worry about element locators and providing AI-powered adaptation to UI changes.

aicommit is a small command line tool for generating commit messages that follow the repository's existing style. It helps users create commit messages with intention, context, and external references to aid understanding of code changes. The tool offers flags like `-c` for adding context and supports retrying and dry-running commit messages. Users can also provide context to the AI for better message generation and save API key to disk for convenience. aicommit reads a `COMMITS.md` file to determine the style guide, following it if available.

Vespa documentation is served using GitHub Project pages with Jekyll. To edit documentation, check out and work off the master branch in this repository. Documentation is written in HTML or Markdown. Use a single Jekyll template _layouts/default.html to add header, footer and layout. Install bundler, then $ bundle install $ bundle exec jekyll serve --incremental --drafts --trace to set up a local server at localhost:4000 to see the pages as they will look when served. If you get strange errors on bundle install try $ export PATH=“/usr/local/opt/[email protected]/bin:$PATH” $ export LDFLAGS=“-L/usr/local/opt/[email protected]/lib” $ export CPPFLAGS=“-I/usr/local/opt/[email protected]/include” $ export PKG_CONFIG_PATH=“/usr/local/opt/[email protected]/lib/pkgconfig” The output will highlight rendering/other problems when starting serving. Alternatively, use the docker image `jekyll/jekyll` to run the local server on Mac $ docker run -ti --rm --name doc \ --publish 4000:4000 -e JEKYLL_UID=$UID -v $(pwd):/srv/jekyll \ jekyll/jekyll jekyll serve or RHEL 8 $ podman run -it --rm --name doc -p 4000:4000 -e JEKYLL_ROOTLESS=true \ -v "$PWD":/srv/jekyll:Z docker.io/jekyll/jekyll jekyll serve The layout is written in denali.design, see _layouts/default.html for usage. Please do not add custom style sheets, as it is harder to maintain.

Shell-AI (`shai`) is a CLI utility that enables users to input commands in natural language and receive single-line command suggestions. It leverages natural language understanding and interactive CLI tools to enhance command line interactions. Users can describe tasks in plain English and receive corresponding command suggestions, making it easier to execute commands efficiently. Shell-AI supports cross-platform usage and is compatible with Azure OpenAI deployments, offering a user-friendly and efficient way to interact with the command line.

Flux All-In-One is a lightweight distribution optimized for running the GitOps Toolkit controllers as a single deployable unit on Kubernetes clusters. It is designed for bare clusters, edge clusters, clusters with restricted communication, clusters with egress via proxies, and serverless clusters. The distribution follows semver versioning and provides documentation for specifications, installation, upgrade, OCI sync configuration, Git sync configuration, and multi-tenancy configuration. Users can deploy Flux using Timoni CLI and a Timoni Bundle file, fine-tune installation options, sync from public Git repositories, bootstrap repositories, and uninstall Flux without affecting reconciled workloads.

Autolabel is a Python library designed to label, clean, and enrich text datasets using Large Language Models (LLMs). It provides a simple 3-step process for labeling data, supports various NLP tasks, and offers features like confidence estimation, explanations, and state management. Users can access Refuel hosted LLMs for labeling and confidence estimation, and the library supports commercial and open source LLMs from providers like OpenAI, Anthropic, HuggingFace, and Google. Autolabel aims to streamline the labeling process for machine learning tasks by leveraging state-of-the-art LLM techniques and minimizing costs and experimentation time.

Gollama is a tool designed for managing Ollama models through a Text User Interface (TUI). Users can list, inspect, delete, copy, and push Ollama models, as well as link them to LM Studio. The application offers interactive model selection, sorting by various criteria, and actions using hotkeys. It provides features like sorting and filtering capabilities, displaying model metadata, model linking, copying, pushing, and more. Gollama aims to be user-friendly and useful for managing models, especially for cleaning up old models.

DIAL Chat is a default UI for AI DIAL, recommended for learning the capability of the headless system. It offers various features like IDP support, model comparison, DIAL extensions, conversation replays, and branding. Managed as a monorepo by NX tools, it provides documentation for DIAL Chat, Theming, Overlay, and Visualizer Connector. Users can find a user guide for the AI DIAL Chat application in the AI DIAL repository.

llm2sh is a command-line utility that leverages Large Language Models (LLMs) to translate plain-language requests into shell commands. It provides a convenient way to interact with your system using natural language. The tool supports multiple LLMs for command generation, offers a customizable configuration file, YOLO mode for running commands without confirmation, and is easily extensible with new LLMs and system prompts. Users can set up API keys for OpenAI, Claude, Groq, and Cerebras to use the tool effectively. llm2sh does not store user data or command history, and it does not record or send telemetry by itself, but the LLM APIs may collect and store requests and responses for their purposes.

Aphrodite is an inference engine optimized for serving HuggingFace-compatible models at scale. It leverages vLLM's Paged Attention technology to deliver high-performance model inference for multiple concurrent users. The engine supports continuous batching, efficient key/value management, optimized CUDA kernels, quantization support, distributed inference, and modern samplers. It can be easily installed and launched, with Docker support for deployment. Aphrodite requires Linux or Windows OS, Python 3.8 to 3.12, and CUDA >= 11. It is designed to utilize 90% of GPU VRAM but offers options to limit memory usage. Contributors are welcome to enhance the engine.

fount is a character card frontend page that decouples AI sources, AI characters, user personas, dialogue environments, and AI plugins, allowing them to be freely combined to spark infinite possibilities. It serves as a bridge connecting imagination and reality, a lighthouse guiding characters and stories, and a free garden for AI sources, characters, personas, dialogue environments, and plugins to grow and bloom. It integrates AI sources without the need for reverse proxy servers, improves web experience with features like multi-device synchronization and unfiltered HTML rendering, and extends companionship beyond the web by connecting characters to Discord groups and providing gentle reminders through fount-pwsh. For character creators, fount offers infinite possibilities with JavaScript or TypeScript code customization, execution of code without filtering, loading npm packages, and creating custom HTML pages. It encourages extension through modularization and community contributions.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

Fabric is an open-source framework for augmenting humans using AI. It provides a structured approach to breaking down problems into individual components and applying AI to them one at a time. Fabric includes a collection of pre-defined Patterns (prompts) that can be used for a variety of tasks, such as extracting the most interesting parts of YouTube videos and podcasts, writing essays, summarizing academic papers, creating AI art prompts, and more. Users can also create their own custom Patterns. Fabric is designed to be easy to use, with a command-line interface and a variety of helper apps. It is also extensible, allowing users to integrate it with their own AI applications and infrastructure.

The user interface (and the main server) of the simulator of aids and social benefits for young people. It is based on the free socio-fiscal simulator Openfisca.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

Eval-Scope is a framework for evaluating and improving large language models (LLMs). It provides a set of commonly used test datasets, metrics, and a unified model interface for generating and evaluating LLM responses. Eval-Scope also includes an automatic evaluator that can score objective questions and use expert models to evaluate complex tasks. Additionally, it offers a visual report generator, an arena mode for comparing multiple models, and a variety of other features to support LLM evaluation and development.

Groq Cloud runs LLM models fast and cheap. Llama 3, Mixtrel, Gemma, and more at hundreds of tokens per second, at cents per million tokens.

Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups.

Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

Informative and expert advice on clothes dryers and their usage.

Exactly like "Laundry Buddy", but evil 😈

Ask me anything about stains, settings, sorting and everything laundry.

Provides detailed information on the fan industry.

Gives you a Joker for Dry January, but only if you can convince her...

Constructs and iteratively improves DryMerge YAML workflows.

Dry-witted 1950s space adventure.

dry-humor, story-driven, introspective conversations

Provides dry, accurate answers in a formal tone.

A helpful Assistant with a bit of dry British humour.

Recommends Japanese sake based on meal descriptions or photos.Sake is difficult because there are different kinds of sake, such as sweet and dry. Therefore, they suggest what kind of sake is recommended for the current meal.

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Expert on Atopic Dermatitis research, focusing on scientifically validated information.