Gemma 3n model: Details
Gemma 3n model: Key capabilities
- Audio input: The model can process sound-based data, enabling applications like speech recognition, language translation, and audio analysis.
- Multimodal input: With support for visual, text, and audio inputs, the model can handle complex tasks that involve combining different types of data.
- Broad language support: Google said that the model is trained in over 140 languages.
- 32K token context window: Gemma 3n supports input sequences up to 32,000 tokens, allowing it to handle large chunks of data in one go—useful for summarising long documents or performing multi-step reasoning.
- PLE caching: The model’s internal components (embeddings) can be stored temporarily in fast local storage (like the device’s SSD), helping reduce the RAM needed during repeated use.
- Conditional parameter loading: If a task doesn’t require audio or visual capabilities, the model can skip loading those parts, saving memory and speeding up performance.
Gemma 3n model: Availability
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