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            ## How it works
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            This demo sets up a simple web server to host a frontend where users can enter a text prompt. This starts a generation process in a web worker to avoid blocking the main UI thread. The worker uses a bundled version of the MediaPipe Tasks GenAI package ([@mediapipe/tasks-genai](https://www.npmjs.com/package/@mediapipe/tasks-genai)) to generate a response from the model and send it back to the user.
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            **Requirements:** Browser with [WebGPU support](https://caniuse.com/webgpu)
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            ## Resources
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            * [Notebook: Fine-tune Gemma 3 270M](https://github.com/google-gemini/gemma-cookbook/blob/main/Demos/Emoji-Gemma-on-Web/resources/Fine_tune_Gemma_3_270M_for_emoji_generation.ipynb)
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            * [Notebook: Convert Gemma 3 270M for use with MediaPipe](https://github.com/google-gemini/gemma-cookbook/blob/main/Demos/Emoji-Gemma-on-Web/resources/Convert_Gemma_3_270M_to_LiteRT_for_MediaPipe_LLM_Inference_API.ipynb)
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            * [MediaPipe LLM Inference Web documentation](https://ai.google.dev/edge/mediapipe/solutions/genai/llm_inference/web_js)
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            title: Emoji Generator
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            emoji: ✨
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            colorFrom: blue
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            sdk: static
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            short_description: Translate text to emojis with Gemma 3 270M running on-device
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            ---
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            This demo runs a fine-tuned Gemma 3 270M model client-side using MediaPipe LLM Inference API. After the initial download, the model is cached by the browser, allowing for offline inference and instant loading and on future visits.
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                    </div>
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                </div>
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                    <p>Powered by <a href="https://goo.gle/hf-gemma-3-270m-it">Gemma 3 270M</a> and <a href="https://ai.google.dev/edge/mediapipe/">MediaPipe</a></p>
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                    <a href="https://goo.gle/emoji-gemma-cookbook" target="_blank">View on GitHub<svg fill="none" xmlns="http://www.w3.org/2000/svg"
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