Instructions to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech") - Notebooks
- Google Colab
- Kaggle
File size: 231 Bytes
97023e7 | 1 2 3 4 5 6 7 8 9 10 11 | {
"feature_extractor_type": "SeamlessM4TFeatureExtractor",
"feature_size": 80,
"num_mel_bins": 80,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000,
"stride": 2
}
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