Instructions to use UsefulSensors/moonshine-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UsefulSensors/moonshine-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="UsefulSensors/moonshine-base")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("UsefulSensors/moonshine-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("UsefulSensors/moonshine-base") - Notebooks
- Google Colab
- Kaggle
GGUF + pure-C++ runtime in CrispASR — Moonshine base
#6 opened 18 days ago
by
cstr
Add Open ASR Leaderboard evaluation results
#5 opened about 1 month ago
by
SaylorTwift
Adding ONNX file of this model
#4 opened 10 months ago
by
tehkehyong
Word-level timestamps?
#3 opened 11 months ago
by
hammeiam