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| title: Embedding Explorer | |
| emoji: π | |
| colorFrom: purple | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: "6.5.1" | |
| app_file: app.py | |
| pinned: false | |
| # Embedding Explorer | |
| Interactive word vector visualization for the Responsible AI course at Huston-Tillotson University. | |
| ## Features | |
| - **Explore** β Type words, see them in 3D space. Similar words cluster together. Click a word to see its nearest neighbors. | |
| - **Vector Math** β Word arithmetic like `king - man + woman β queen`. Results reveal hidden relationships encoded in the vectors. | |
| ## Configuration | |
| All examples are configurable via HuggingFace Space environment variables (no code changes needed): | |
| | Variable | Default | Description | | |
| |----------|---------|-------------| | |
| | `EXPLORE_EXAMPLES` | `["dog cat fish car truck", ...]` | JSON list of word groups for Explore tab | | |
| | `ARITHMETIC_EXAMPLES` | `["king - man + woman", ...]` | JSON list of expressions for Vector Math tab | | |
| | `N_NEIGHBORS` | `8` | Number of nearest neighbors to show on click | | |
| ## Model | |
| Uses [GloVe](https://nlp.stanford.edu/projects/glove/) (Global Vectors for Word Representation) trained on Wikipedia + Gigaword β 400K words, 300 dimensions. Downloaded automatically on first startup via gensim (~376 MB, cached for subsequent runs). | |
| ## Course | |
| Responsible AI: Technology, Power, and Justice (COSC-2300A) | |
| Huston-Tillotson University, Spring 2026 | |
| Instructor: Chris Hyams | |