Instructions to use eustlb/moonshine-streaming-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eustlb/moonshine-streaming-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eustlb/moonshine-streaming-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("eustlb/moonshine-streaming-tiny") model = AutoModelForMultimodalLM.from_pretrained("eustlb/moonshine-streaming-tiny") - Notebooks
- Google Colab
- Kaggle
File size: 310 Bytes
ea4402f | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"feature_extractor": {
"do_normalize": false,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000
},
"processor_class": "MoonshineStreamingProcessor"
}
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