oobabooga/text-generation-webui

Features

• Local Inference Engines - Executes large language models locally using optimized machine learning backends.
• Local Model Runtimes - Enables private, offline execution of large language models on local hardware.
• Model Serving APIs - Expose local language models through a standard API interface to integrate text generation capabilities into your own custom software applications and external development workflows.
• Local Model Management - Maintain data privacy by running language models entirely offline while controlling settings and user interactions through a dedicated web-based interface designed for local model management.
• Model Inference Servers - Exposes local language model inference capabilities through standard API endpoints for external integration.
• Text Generation - Creates text and chat interactions using local language models and custom templates.
• AI Integration Interfaces - Exposing local text generation capabilities through standard interfaces to incorporate advanced language processing into your own custom software applications.
• Conversational Interfaces - Provides tools for building and testing conversational interfaces using custom prompt templates and chat modes.
• Model Fine-Tuning - Provides a unified interface for training and adjusting model parameters for specialized tasks.
• Containerization Tools - Run software inside isolated containers to ensure consistent performance and simplified dependency management across different host operating systems without requiring manual configuration of the underlying environment.
• Generative AI Dashboards - Provides a web-based graphical dashboard for managing and interacting with offline generative text models.
• Machine Learning Environment Managers - Simplifying the setup and isolation of complex machine learning dependencies to ensure consistent performance across different host operating systems and hardware.
• AI & Machine Learning - Web interface for running large language models locally.
• Chat Interfaces - Gradio-based web interface for interacting with LLMs.
• Generative AI and Diffusion - Offline local interface for running large language models.
• Inference and Serving - Gradio-based web interface for model inference.
• Large Language Models - Versatile web interface for running multiple LLM architectures.
• LLM Development and Research - Gradio-based web interface for running various language models.
• Open Source Models - Provides a web interface for running various local models.
• User Interfaces - Advanced UI with extensive backend and feature support.
• Model Deployment - Listed in the “Model Deployment” section of the Llm Course awesome list.
• RESTful APIs - Exposes internal model inference capabilities through a standardized network interface.
• Model Fine-Tuning Environments - Provides a unified environment for training and customizing language models using local compute resources.
• Web-Based Control Panels - Provides a browser-based interface to manage model loading and generation parameters.
• Command Line Interfaces - Adjust application behavior at launch by passing command-line arguments to define network ports, file paths, and hardware acceleration settings for your specific computing environment.
• Environment Managers - Isolate project libraries and package versions using a dedicated environment manager to ensure consistent compatibility and reliable execution across different development or production host systems.
• AI Deployment Containers - Offers a portable containerized stack for consistent execution of machine learning workflows.
• Containerization - Packages the application and dependencies into isolated images for consistent deployment.

Star history