NSFW JS

NSFW JS

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Website: nsfwjs.com

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NSFW JS is an adult-oriented AI chat platform designed to provide users with personalized and immersive interactions. The app focuses on delivering a tailored experience through advanced AI technology, allowing users to engage in various types of conversations. Key features include customizable character options, scenario-based roleplay capabilities, and the ability to create unique interactions based on user preferences.

The app leverages AI models to understand and respond to user inputs, offering a realistic and engaging experience. Users can explore different themes and scenarios, from casual chats to more intimate interactions, all within a secure and user-friendly environment. The app's design emphasizes user customization, allowing individuals to personalize their experience by selecting specific tones, themes, and interaction styles.

NSFW JS aims to provide a seamless and interactive experience, utilizing voice and text capabilities to mimic human-like conversations. The app's focus on personalization and adaptability makes it suitable for users seeking a more immersive and engaging adult chat experience. By incorporating AI-driven character creation and scenario-based conversations, NSFW JS offers a unique blend of technology and interactivity, catering to diverse user preferences and needs.

NSFWJS is a JavaScript library designed to help identify potentially inappropriate images on a client's browser, without needing to send the image to a server. The library is powered by TensorFlowJS, which is an open-source machine learning library for JavaScript. The library is trained to recognize particular patterns in the images, with the current accuracy rate at 93%. The library also incorporates CameraBlur Protection, which is a feature that blurs any images that it identifies as being potentially inappropriate. The library is constantly being improved and updated, with new models being released frequently. NSFWJS is free to use, and can be modified and distributed under the MIT license. The library also includes a mobile demo, which allows users to test different images on their mobile devices. Finally, the library is available for download through GitHub, and users are encouraged to report any false positives or contribute to the development of the library.

Website: nsfwjs.com

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