Instructions to use moonshine-ai/moonshine-base-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonshine-ai/moonshine-base-vi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="moonshine-ai/moonshine-base-vi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("moonshine-ai/moonshine-base-vi") model = AutoModelForSpeechSeq2Seq.from_pretrained("moonshine-ai/moonshine-base-vi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2b14b75079970e4066a07f80a580101acc6e76abc009b8442adfe7669f9ce5d
- Size of remote file:
- 246 MB
- SHA256:
- 6c083e3a8ad5e8aa411af3e4f43b71ef9215be8ceb8cfc3f745803c76d3a8268
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.