---
library_name: torq
tags:
- Automatic Speech Recognition
- Astra SL
- SL2600
- MPU
license: mit
base_model:
- Synaptics/Moonshine
base_model_relation: quantized
---

# Moonshine Tiny 

## Model Overview

Moonshine is a high-efficiency automatic speech recognition (ASR) model designed specifically for real-time speech recognition. Unlike Whisper, which processes audio in fixed 30-second chunks, Moonshine uses a variable-length architecture that only computes the actual duration of the speech received. 

Useful Sensors developed Moonshine and released the English model as open-source. There are 2 models of different sizes and capabilities - base and tiny. The tiny version utilizes 27M parameters. 


Moonshine Tiny has been optimized for the Synaptics Astra™ **SL2610-Series processors** with Torq NPU.

## Model Features
- **Model Type:** Automatic Speech Recognition
- **Input:** Raw waveform (1D array of floats) 16kHz mono audio up to 30 seconds
- **Output:** Sequence of token IDs (integers)


## Deployment

The compiled model files are available for download on Huggingface at [Synaptics/Moonshine](https://huggingface.co/Synaptics/Moonshine).

Usage tutorial to be available in the future at [Synaptics AI Developer Zone](https://developer.synaptics.com/docs/sl/sl2600/introduction).


## License

Both the source model and the compiled model for on-device deployment are licensed under [MIT License](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/mit.md).

## Learn More

- [Synaptics AI Developer Zone](https://developer.synaptics.com?utm_source=hf): Get started with documentation, tutorials and resources for your Edge AI journey.
- [Astra Support Portal](https://synacsm.atlassian.net/servicedesk/customer/portal/543?utm_source=hf): Connect with our engineering team and community.