• Award-Winning Medical Office Software Designed for Your Specialty Icon
    Award-Winning Medical Office Software Designed for Your Specialty

    Succeed and scale your practice with cloud-based, data-backed, AI-powered healthcare software.

    RXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
    Learn More
  • The Most Powerful Software Platform for EHSQ and ESG Management Icon
    The Most Powerful Software Platform for EHSQ and ESG Management

    Addresses the needs of small businesses and large global organizations with thousands of users in multiple locations.

    Choose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
    Learn More
  • 1
    SillyTavern

    SillyTavern

    LLM Frontend for Power Users

    Mobile-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI, OpenRouter, Claude, Scale), VN-like Waifu Mode, Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters...
    Downloads: 354 This Week
    Last Update:
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  • 2
    Transformer Explainer

    Transformer Explainer

    Learn How LLM Transformer Models Work with Interactive Visualization

    Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward networks. Users can observe how attention weights change as the model predicts the next token, offering insight into how transformer architectures capture relationships between words. ...
    Downloads: 0 This Week
    Last Update:
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