Instructions to use litert-community/moonshine-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/moonshine-tiny with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Link the Android speech recognition sample app
Browse files
README.md
CHANGED
|
@@ -175,6 +175,12 @@ if __name__ == "__main__":
|
|
| 175 |
python transcribe.py --wav sample.wav
|
| 176 |
```
|
| 177 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 178 |
## Performance
|
| 179 |
|
| 180 |
Measured on one 5 s window of continuous speech (11 output tokens), CPU
|
|
|
|
| 175 |
python transcribe.py --wav sample.wav
|
| 176 |
```
|
| 177 |
|
| 178 |
+
### Android sample app
|
| 179 |
+
|
| 180 |
+
For an on-device Android demo that runs Moonshine (and other ASR models) with
|
| 181 |
+
hardware acceleration, see the LiteRT
|
| 182 |
+
[speech recognition sample](https://github.com/google-ai-edge/litert-samples/tree/main/samples/litert/speech_recognition).
|
| 183 |
+
|
| 184 |
## Performance
|
| 185 |
|
| 186 |
Measured on one 5 s window of continuous speech (11 output tokens), CPU
|