Instructions to use facebook/mms-tts-nan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-nan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-nan")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-nan") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-nan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/mms-tts-nan: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/facebook/mms-tts-nan/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/mms-tts-nan/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/mms-tts-nan/resolve/main/pytorch_model.bin
145 MB
- Xet hash:
- 5ea8fde91eaa8534146bc2e675ec2f9ab4504576cbba29b720d3a6797db585a3
- Size of remote file:
- 145 MB
- SHA256:
- 4c768bd1e35a2fb921dac095d83ee7411502da084b4e124a5f1dd1d3151cc8ef
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