Instructions to use Matthijs/mms-tts-kor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/mms-tts-kor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Matthijs/mms-tts-kor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-kor") model = AutoModelForTextToWaveform.from_pretrained("Matthijs/mms-tts-kor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Matthijs/mms-tts-kor: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/Matthijs/mms-tts-kor/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Matthijs/mms-tts-kor/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Matthijs/mms-tts-kor/resolve/main/pytorch_model.bin
145 MB
- Xet hash:
- 1a1d5f844f609f93ce7cb3fbeb867aab0a7fc86ca64b40a859ac3bf883488c68
- Size of remote file:
- 145 MB
- SHA256:
- d42b0cd5fd3451f3cac34151d6f851e1d6337d9607107353acbb58333b31f5a7
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