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| title: Beam Search Demo | |
| emoji: 🌍 | |
| colorFrom: green | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: 5.16.2 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Beam Search vs Greedy Search Demo | |
| Welcome to the Beam Search vs Greedy Search Demo repository! This educational demo illustrates two text generation strategies in LLM inference using the Qwen2.5-0.5B model. | |
| This demo compares: | |
| - **Greedy Search**: Picks the most probable token at every generation step (deterministic). | |
| - **Beam Search**: Explores multiple beams concurrently and returns the top candidate, often achieving more coherent or creative outputs. | |