Text Generation Web UI AI technology page Top Builders

Explore the top contributors showcasing the highest number of Text Generation Web UI AI technology page app submissions within our community.

Text Generation Web UI

The Text Generation Web UI is a Gradio-based interface for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA. It provides a user-friendly interface to interact with these models and generate text, with features such as model switching, notebook mode, chat mode, and more. The project aims to become the go-to web UI for text generation and is similar to AUTOMATIC1111/stable-diffusion-webui in terms of functionality.

Features

Dropdown menu for switching between models
Notebook mode that resembles OpenAI's playground
Chat mode for conversation and role-playing
Instruct mode compatible with various formats, including Alpaca, Vicuna, Open Assistant, Dolly, Koala, ChatGLM, and MOSS
Nice HTML output for GPT-4chan
Markdown output for GALACTICA, including LaTeX rendering
Custom chat characters
Advanced chat features (send images, get audio responses with TTS)
Efficient text streaming
Parameter presets
Layers splitting across GPU(s), CPU, and disk
CPU mode
and much more!

Installation

There are different installation methods available, including one-click installers for Windows, Linux, and macOS, as well as manual installation using Conda. Detailed installation instructions can be found in the Text Generation Web UI repository.

Downloading Models

Models should be placed inside the models folder. You can download models from Hugging Face, such as Pythia, OPT, GALACTICA, and GPT-J 6B. Use the download-model.py script to automatically download a model from Hugging Face.

Starting the Web UI

After installing the necessary dependencies and downloading the models, you can start the web UI by running the server.py script. The web UI can be accessed at http://localhost:7860/?__theme=dark. You can customize the interface and behavior using various command-line flags.

System Requirements

Check the wiki for examples of VRAM and RAM usage in both GPU and CPU mode.

Contributing

Pull requests, suggestions, and issue reports are welcome. Before reporting a bug, make sure you have followed the installation instructions provided and searched for existing issues.

Edit on Github

Text Generation Web UI AI technology page Hackathon projects

Discover innovative solutions crafted with Text Generation Web UI AI technology page, developed by our community members during our engaging hackathons.

Quantum-Scribe

Quantum-Scribe is a pioneering AI project that pushes the boundaries of content creation. Leveraging the power of natural language processing and deep learning, our system generates well-structured, coherent manuscripts, reports, and articles on a wide range of topics. Whether you're a student, researcher, or writer, Quantum-Scribe streamlines the writing process, enabling you to focus on ideas and insights rather than struggling with words. Our project is poised to transform how information is documented, shared, and disseminated in various fields. Join us in reshaping the future of written communication.

Llamarizer

Introducing "Llamarizer," a dynamic text summarization tool fueled by the potent Llama2-13b model crafted by Meta AI. Leveraging the robust capabilities of the Clarifai platform, our app represents our earnest entry into the "Llama2 Hackathon with Clarifai," thoughtfully organized by LabLab. In a world overwhelmed by information, "Llamarizer" seeks to empower users with the ability to transform extensive text into concise, coherent summaries, revolutionizing the way content is absorbed and understood. Join us on this journey to enhance efficiency and elevate your content consumption experience.

Building Your Own Jarvis

JARVIS acts as an intelligent intermediary between users and a network of specialized agents. When a user interacts with the system, their message is directed to JARVIS as the primary point of contact. This initial step is where the magic begins to unfold. After understanding the user need. JARVIS navigates through a repository of specialized agents, each programmed to excel in specific tasks. Whether it's fetching information, performing calculations, or executing complex actions, JARVIS knows just the right agent for the job. Upon identifying the ideal agent, JARVIS initiates a seamless handover. The chosen agent becomes active, taking on the responsibility of fulfilling the user's request. This activation process extends to both the frontend and backend components, ensuring a cohesive and synchronized interaction between the user, JARVIS, and the chosen agent. Rather than users needing to interact with multiple agents individually, JARVIS simplifies the experience by acting as a gatekeeper. Users interact with a single point of contact, making their queries and requests in natural language, while JARVIS handles the intricate orchestration behind the scenes. To exhibit our system's potential, we've crafted a user-friendly web interface, sidestepping authentication complexities. Inside, two prototype agents—"music" and "call"—showcase our concept's prowess. As we look towards the future, our vision encompasses the integration of an expanding repertoire of specialized agents. This entails leveraging the power of prompt engineering to craft prompts that elicit precise and effective responses from the agents. By refining these prompts and training the agents, we aim to elevate the system's accuracy and versatility, enabling it to address an ever-widening array of user needs and inquiries.

Real Time Language Translation for video calls

1. Technologies used : a. Eleven Labs Whisper : speech recognition and translation model for real time language translation b. Eleven Labs Voice AI : generates natural & life like voice that speaks out translated text almost simultaneously 2. Existing Technologies and their Limitations : a) Skype Translator : Less accurate due to complex accents => miscommunication b) Google meet's live caption : Used only for live captions , not accurate for complex language translation c) Zoom language Interpretation : Limited availability & higher cost. 3. Unique Selling Proposition - unlike existing technologies that focus on text based translation - we will provide natural life like voice translations for effective & interactive communication 4.How will we build? i. develop environment + frameworks, libraries ii. integrate whisper's speech recognition iii. implement video call functionality iv. use Voice AI to generate voice output for translated text and play it v. test our application to ensure accuracy vi. optimize app's performance and user experience vii. Deploy the app on server / cloud platform 5. Real Life Use Cases : ✅. Multilingual Business Meetings ✅ Language Exchange Programs ✅ Virtual Language Education ✅Cross cultural Collaboration ✅Global Customer Support Teams. ✅International Virtual Event

Pixelcrafters - Chats with GIF Recommendations

PixelCrafters is an innovative chat application that aims to elevate chat conversations by seamlessly integrating AI-powered GIF recommendations. It utilizes advanced language models and AI algorithms to analyze the content of chat conversations. It self-analyzes the ongoing chat dialogue, generating contextually relevant responses that align with the flow and tone of the conversation. By understanding the context, PixelCrafters intelligently suggests the most suitable GIFs that complement the text, enhancing the expressiveness of the chat. The application leverages the power of cosine similarity calculations to match the generated response with a database of GIPHY captions. This ensures that the recommended GIFs are highly relevant and closely aligned with the chat content. Users can easily select and share the suggested GIFs within the chat platform, adding a touch of creativity and emotion to their conversations.

GhaGeni

GhaGeni is developed using Web Assembly (WSAM) and Flutter. It incorporatesGoogle Cloud's large language model (Palm2 )for intelligent conversations. The user interface is designed for a seamless experience. GhaGeni utilizes a Redis database for efficient data management and prompt storage. The core idea behind GhaGeni is to provide users with a fresh perspective and help them overcome mental roadblocks by asking thought-provoking questions. It recognizes that individuals often struggle to remember crucial details or fully explore different angles when working on complex tasks. GhaGeni steps in to bridge that gap and facilitate a more fruitful and efficient problem-solving experience. When a user engages with GhaGeni, they begin by stating their objective or desired outcome. It could be anything from designing a website to planning a marketing campaign. GhaGeni then responds with a set of three questions related to the user's objective. These questions are carefully crafted to prompt the user to consider various aspects, explore different angles, and uncover hidden insights. As the user responds to each question, GhaGeni dynamically generates the next set of three questions based on their previous answers. This iterative process guides the user down a path of continuous discovery and exploration. The questions become increasingly tailored and specific to the user's unique needs, enabling them to dive deeper into their project and consider aspects they may have overlooked. Whether you're a professional working on a complex project, a student grappling with an academic task, or an individual looking for inspiration and guidance, GhaGeni is there to support you every step of the way. Embrace the power of interactive conversations and unlock your true genius with GhaGeni.