Instructions to use moonshine-ai/moonshine-base-uk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonshine-ai/moonshine-base-uk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="moonshine-ai/moonshine-base-uk")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("moonshine-ai/moonshine-base-uk") model = AutoModelForSpeechSeq2Seq.from_pretrained("moonshine-ai/moonshine-base-uk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9211f34a1c56f8399d103ca10deb105455d5e50f2982b17ac6b109b1794bddd9
- Size of remote file:
- 246 MB
- SHA256:
- 7b4e3c86d83f2710996df7330a3a9c912e8364beb520bef4ba844d7bfb31e94c
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