--- title: Interactive Gemma Text Generation Demo emoji: ✍️ colorFrom: indigo colorTo: blue sdk: streamlit sdk_version: 1.44.1 app_file: app.py pinned: true short_description: Cool and Awesome initial prototype for GSOC Proposal tags: - text-completion - large-language-models - llm - gemma-2b - streamlit - interactive-demo - gsoc - google-deepmind - text-generation - gemma - streamlit - large-language-models - natural-language-processing thumbnail: >- https://cdn-uploads.huggingface.co/production/uploads/67ac255d23491001de30c71c/K2IlTBGqHbnJgYQ5a_-hX.png --- # Gemma Text Generator A streamlined web application that leverages Google's Gemma-2B language model to generate text with customizable tones and parameters. ## Overview This project is a Streamlit-based web application that allows users to generate text using Google DeepMind's Gemma-2B language model. The application features an intuitive interface where users can input prompts, select different tones (Funny, Serious, or Poetic), and adjust various generation parameters to customize the output. ## Features - **Text Generation**: Generate text completions from user prompts - **Tone Selection**: Choose from three different writing styles: - Funny: Witty and humorous responses with unexpected twists - Serious: Thoughtful and professional responses with logical reasoning - Poetic: Vivid, lyrical responses with metaphors and imagery - **Customizable Parameters**: - Word count: Control the approximate length of generated text - Temperature: Adjust the creativity and randomness - Top-p (Nucleus Sampling): Control the diversity of outputs - Repetition Penalty: Prevent repetitive phrases - **Word Cloud Visualization**: See a visual representation of word frequency in the generated text - **One-Click Examples**: Try pre-configured examples with a single click ## Technology Stack - **Streamlit**: Web application framework - **Hugging Face Transformers**: Library for accessing pre-trained language models - **Google Gemma-2B**: The underlying language model for text generation - **PyTorch**: Deep learning framework - **WordCloud**: Library for creating visual representations of text data - **Matplotlib**: For visualizing the word cloud Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference