oobabooga: Text Generation Web UI and APIs

Description

Let me introduce you to the Text Generation Web UI, a fascinating project available on GitHub. If you’re new to AI and exploring open-source AI models, this tool can be a great starting point.

Please start watching the video from 4:00 minutes since we already have a pre-configured setup with Text generation WebUI

Github repo: https://github.com/oobabooga/text-generation-webui

What Is the Text Generation Web UI?

The Text Generation Web UI (often referred to as TGW or oobabooga) is a Gradio-based interface designed for running Large Language Models (LLMs). Here are the key features and concepts you need to know:

1. Purpose:
   • The primary goal of this tool is to provide a user-friendly way to interact with various language models and generate text.
   • It’s especially useful for those who want to experiment with AI-generated content without diving into complex command-line interfaces.
2. Supported Models:
   • The Text Generation Web UI supports a variety of LLMs, including:
     • Transformers: These are popular pre-trained models for natural language understanding and generation.
     • llama.cpp: A powerful language model (through llama-cpp-python) that can be used for text generation.
     • ExLlamaV2: An extended version of llama.cpp.
     • AutoGPTQ and AutoAWQ: These are variants of GPT models.
     • GPTQ-for-LLaMa: A specific adaptation of GPT for llama.cpp.
     • CTransformers: Another transformer-based model.
     • QuIP#: A unique model for text generation.
3. User Interface Modes:
   • The Text Generation Web UI offers three interface modes:
     • Default (Two Columns): A straightforward interface with input and output columns.
     • Notebook Mode: A notebook-style interface for experimentation.
     • Chat Mode: Allows interactive conversations with the model.
4. Model Switching:
   • You can easily switch between different models using a dropdown menu.
   • This flexibility lets you explore various LLMs and compare their outputs.
5. Extensions:
   • The tool supports a wide range of extensions, both built-in and user-contributed.
   • Extensions include features like:
     • Coqui TTS: For realistic voice outputs.
     • Whisper STT: For voice inputs.
     • Translation: To translate text.
     • Multimodal Pipelines: Combining text and other modalities.
     • Vector Databases: For efficient storage and retrieval.
     • Stable Diffusion Integration: A powerful technique for text generation.
6. Chat with Custom Characters:
   • You can create custom characters and engage in chat-based interactions.
   • Precise chat templates are available for instruction-following models.
7. LoRA (Language of Response Agents):
   • You can train new LoRAs with your own data and load/unload them on the fly for text generation.
8. Transformers Library Integration:
   • Load models in 4-bit or 8-bit precision using the bitsandbytes library.
   • Use llama.cpp with transformers samplers (llamacpp_HF loader).
   • Perform CPU inference in 32-bit precision using PyTorch.
9. OpenAI-Compatible API Server:
   • The tool provides an API server with Chat and Completions endpoints.
   • You can explore examples and integrate it into your own projects.