Instructions to use SHENMU007/neunit0424 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit0424 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit0424")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit0424") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit0424") - Notebooks
- Google Colab
- Kaggle
File size: 432 Bytes
b78d81f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"do_normalize": false,
"feature_extractor_type": "SpeechT5FeatureExtractor",
"feature_size": 1,
"fmax": 7600,
"fmin": 80,
"frame_signal_scale": 1.0,
"hop_length": 16,
"mel_floor": 1e-10,
"num_mel_bins": 80,
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "SpeechT5Processor",
"return_attention_mask": true,
"sampling_rate": 16000,
"win_function": "hann_window",
"win_length": 64
} |