Instructions to use facebook/mms-tts-kkj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-kkj with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-kkj")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-kkj") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-kkj", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/mms-tts-kkj: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/facebook/mms-tts-kkj/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/mms-tts-kkj/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/mms-tts-kkj/resolve/main/pytorch_model.bin
145 MB
- Xet hash:
- 8ae34825ec2689b18e3773f05892314222f591107a12670c1d2079d387aa1531
- Size of remote file:
- 145 MB
- SHA256:
- 1d690c213cdf576330baad9d2d1cc9a357894bde29dcbb464d733ea9d01fbef1
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