Instructions to use UsefulSensors/moonshine-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UsefulSensors/moonshine-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="UsefulSensors/moonshine-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("UsefulSensors/moonshine-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("UsefulSensors/moonshine-tiny") - Notebooks
- Google Colab
- Kaggle
Timestamped version?
#4
by hammeiam - opened
I was wondering if it's possible to output the word-level timestamps from this model similar to https://huggingface.co/onnx-community/whisper-base_timestamped
I am wondering the same