Create README.md

README.md

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+---
+base_model: google/gemma-3-270m-it
+library_name: transformers.js
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- onnx
+- gemma
+- gemma-3
+- emoji
+- text-to-emoji
+- conversational
+- web-ready
+license: gemma
+---
+
+
+# Model Card for myemoji-gemma-3-270m-it-onnx
+
+This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it), exported to **ONNX** (Open Neural Network Exchange) format for optimized on-device performance.
+It is designed to act as an "emoji translator," converting input text into relevant emojis.
+
+## Model Details
+
+* **Model Name:** myemoji-gemma-3-270m-it-onnx
+
+* **Base Model:** google/gemma-3-270m-it
+
+* **Architecture:** Gemma 3 (270M parameters)
+
+* **Format:** ONNX (optimized for web/mobile inference)
+
+* **Fine-tuning Task:** Text-to-Emoji translation
+
+* **Language:** English (Input), Emojis (Output)
+
+
+## Intended Use
+
+This model is lightweight (270M parameters) and formatted in ONNX, making it ideal for running directly in the browser (using Transformers.js) or on mobile devices without requiring heavy server-side compute.
+
+### Primary Use Case:
+
+* Translating sentences into emojis (e.g., "I am happy" -> "😊").
+
+* Fun/creative text augmentation in web applications.
+
+## How to Use (Transformers.js)
+
+You can run this model in a web browser using [Transformers.js](https://www.google.com/search?q=https://huggingface.co/docs/transformers.js).
+
+```javascript
+import { pipeline } from '@xenova/transformers';
+
+// Allocate the pipeline
+const generator = await pipeline('text-generation', 'manuelaschrittwieser/myemoji-gemma-3-270m-it-onnx');
+
+// Generate emojis
+const output = await generator('I am so excited for the party!', {
+  max_new_tokens: 20,
+});
+
+console.log(output);
+// Expected output: 😊🎉🎈
+```
+## Training Data
+
+This model was fine-tuned using the Gemma 3 270M Instruction Tuned model as a base. It was likely trained on a dataset of text-emoji pairs to learn the mapping between
+natural language sentiments/objects and their corresponding emoji representations.
+
+## Hardware & Optimization
+
+* **Parameter Count:** 270M (Ultra-compact)
+
+* **Export Format:** ONNX
+
+* **Hardware Compatibility:** CPU, WebGPU, NPU (via ONNX Runtime)
+
+## License
+
+This model is built upon Google's Gemma model. Users must comply with the [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
+
+* **License:** Gemma Terms of Use / Apache 2.0 (Check original base model for specifics)
+
+