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
- Xet hash:
- 5e5c4e97d62084a69032e8928ebc233c62ebbd6c3b9e5cfe9ef13907b0915f65
- Size of remote file:
- 309 kB
- SHA256:
- ef2edf0202d86ed5a90700486811ff5d719002c3d19347cf7fe86b7b81c0f394
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