Instructions to use Matthijs/mms-tts-deu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/mms-tts-deu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Matthijs/mms-tts-deu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-deu") model = AutoModelForTextToWaveform.from_pretrained("Matthijs/mms-tts-deu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Matthijs/mms-tts-deu: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/Matthijs/mms-tts-deu/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Matthijs/mms-tts-deu/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Matthijs/mms-tts-deu/resolve/main/pytorch_model.bin
145 MB
- Xet hash:
- 025c1356c7703a5d1ba8f700a3879b77c0a0bffc237844a820d229791605268f
- Size of remote file:
- 145 MB
- SHA256:
- 1e6d94e93493bdf8779c74f85eda10b8422a6e235d460b76d491279f5b47b5a1
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