Instructions to use moonshine-ai/moonshine-tiny-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonshine-ai/moonshine-tiny-ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="moonshine-ai/moonshine-tiny-ja")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("moonshine-ai/moonshine-tiny-ja") model = AutoModelForSpeechSeq2Seq.from_pretrained("moonshine-ai/moonshine-tiny-ja", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bcd0b1914e0b34d50669f698fbccaf18541fce5a7c4eb1d0d383a556fdf785a
- Size of remote file:
- 108 MB
- SHA256:
- 59a3138090fac9903210cf0f5839bbfbba385940d6b33dca4483495e96be79d3
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