google-deepmind
[Demo] Gemma 2.0 Interactive Demo – Progress, Documentation & Upcoming Features
Hi Gemma Maintainers and Community,
I'm excited to share my interactive demo built on Hugging Face Spaces that leverages the Gemma model. This demo is about 50% complete and already demonstrates several of Gemma's key capabilities. In addition, I’m actively developing a "Playground" and "Deep Dive" section to further compare multiple LLM instances, including older versions and the latest Gemma 3, and to reveal insights into the inner workings of model prompting and response generation.
Implemented Features
-
Overview Page
- Purpose: Provides a high-level introduction to the project and demo.
- Details:
- Built using Streamlit Elements with a custom dashboard layout.
- Includes project branding, key stats, and navigation.
- Challenge: Customization was difficult due to Streamlit's limitations with native JS.
- Reference: overview.py
-
Text Generation Module
- Purpose: Allows users to experiment with various text generation modes of Gemma.
- Details:
- Users can adjust parameters (temperature, top-p, repetition penalty, max token length) and view generated responses.
- Reference: text_generation.py
-
Conversation Module
- Purpose: Implements a one-on-one chat interface with conversation retention.
- Details:
- Maintains session-based conversation for continuous dialogue.
- Reference: qa.py
-
Code Assistance Module
- Purpose: Offers AI-powered code suggestions and modifications.
- Details:
- Integrated the Monaco editor using Streamlit Elements.
- Provides inline suggestions and a modification chat.
- Current Limitation: GitHub ghost text suggestions are shown below the editor; inline integration is under exploration.
- Reference: code.py
Work in Progress & Upcoming Features
-
Playground for Model Comparison
- Description:
- This section will serve as a playground where users can compare multiple LLM instances.
- It will include older versions of Gemma alongside the latest Gemma 3.
- Users will be able to run various tasks side by side, comparing performance and output quality across versions.
- Description:
-
Deep Dive into Model Internals
- Description:
- A detailed section that visually breaks down the inner workings of Gemma.
- What to Expect:
- Visualization of prompt processing and response generation.
- An explanation of function calling and intermediate steps.
- Insight into how embeddings are matched and token-level decisions are made.
- A live “debug mode” that shows the hidden workings of the model (e.g., logits, sampling distributions, etc.).
- Description:
-
GitHub Ghost Text Integration Improvement
- Description:
- Continue working on displaying inline suggestions directly in the Monaco editor.
- Description:
Call to Action
I’d appreciate feedback on both the current demo and these upcoming features:
- Feature Enhancements: Suggestions for improving the UI, interactions, or visualizations.
- Integration Ideas: How to better showcase Gemma’s inner workings and model comparisons.
- Collaboration: Opportunities for joint work or community contributions to further refine the demo.
You can check out the live demo on Hugging Face Spaces here: Live Demo
Thank you for your time and consideration. I’m looking forward to hearing your thoughts and suggestions!
Best regards, Anand Roy
Added Feature:
- Suggestive AI prompts
- Allowed AI to change coding language, and respective code syntax highlighting
@Conchylicultor Could I get some feedback if possible, on ways to improve or stuff that I should add more to the checklist?
Hi @andycandy ,
The planned Playground for model comparison and Deep Dive into Model Internals are particularly exciting features that will offer significant value to the community, moving beyond simple generation to true model analysis.
For immediate feedback, consider making the parameter adjustments more visual (e.g., a dynamic chart showing the effect of temperature on response diversity).
Thanks.
