Instructions to use seba3y/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seba3y/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="seba3y/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("seba3y/whisper-tiny") model = AutoModelForAudioClassification.from_pretrained("seba3y/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 336 Bytes
0534aa7 049a697 0534aa7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"chunk_length": 6,
"feature_extractor_type": "WhisperFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 400,
"n_samples": 96000,
"nb_max_frames": 600,
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "WhisperProcessor",
"return_attention_mask": false,
"sampling_rate": 16000
}
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