Automatic Speech Recognition
Transformers
Safetensors
English
moonshine
quantization-aware-training
int8
riscv
edge
Instructions to use CobbledSteel/moonshine-tiny-qat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CobbledSteel/moonshine-tiny-qat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CobbledSteel/moonshine-tiny-qat")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CobbledSteel/moonshine-tiny-qat") model = AutoModelForSpeechSeq2Seq.from_pretrained("CobbledSteel/moonshine-tiny-qat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 215 Bytes
5d5f6ff | 1 2 3 4 5 6 7 8 9 10 | {
"do_normalize": false,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000
}
|