| # EmbeddingGemma-300M (NPU) - Android Devices | |
| ## Model Description | |
| **EmbeddingGemma** is a 300M-parameter open embedding model developed by **Google DeepMind**. | |
| It is built from **Gemma 3** (with T5Gemma initialization) and the same research and technology used in **Gemini models**. | |
| The model produces **vector representations of text**, making it well-suited for **search, retrieval, classification, clustering, and semantic similarity tasks**. | |
| It was trained on **100+ languages** with ~320B tokens, optimized for **on-device efficiency** (mobile, laptops, desktops). | |
| ## Features | |
| - **Compact and efficient**: 300M parameters, optimized for on-device use. | |
| - **Multilingual**: trained on 100+ spoken languages. | |
| - **Flexible embeddings**: default dimension **768**, with support for **512, 256, 128** via Matryoshka Representation Learning (MRL). | |
| - **Wide task coverage**: retrieval, QA, fact-checking, classification, clustering, similarity. | |
| - **Commercial-friendly**: open weights available for research and production. | |
| ## Use Cases | |
| - Semantic similarity and recommendation systems | |
| - Document, code, and web search | |
| - Clustering for organization, research, and anomaly detection | |
| - Classification (e.g., sentiment, spam detection) | |
| - Fact verification and QA embeddings | |
| - Code retrieval for programming assistance | |
| ## Inputs and Outputs | |
| **Input**: | |
| - **Type**: Text string (e.g., query, prompt, document) | |
| - **Max Length**: 2048 tokens | |
| **Output**: | |
| - **Type**: Embedding vector (default 768d) | |
| - **Options**: 512 / 256 / 128 dimensions via truncation & re-normalization (MRL) | |
| ## Limitations & Responsible Use | |
| This model has known limitations: | |
| - **Bias & coverage**: quality depends on training data diversity. | |
| - **Nuance & ambiguity**: may struggle with sarcasm, figurative language. | |
| - **Ethical concerns**: risk of bias perpetuation, privacy leakage, or malicious misuse. | |
| Mitigations: | |
| - CSAM and sensitive data filtering applied. | |
| - Users should adhere to **Gemma Responsible AI guidelines** and **Prohibited Use Policy**. | |
| ## License | |
| This model is released under the **Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0)** license. | |
| Non-commercial use, modification, and redistribution are permitted with attribution. | |
| For commercial licensing, please contact **dev@nexa.ai**. | |
| ## References | |
| - [nexaSDK](https://sdk.nexa.ai) | |
| ## Support | |
| For SDK-related issues, visit [sdk.nexa.ai](https://sdk.nexa.ai). | |
| For model-specific questions, open an issue in this repository. |