Instructions to use facebook/mms-tts-ory with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-ory with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-ory")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-ory") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-ory", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/mms-tts-ory: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/facebook/mms-tts-ory/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/mms-tts-ory/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/mms-tts-ory/resolve/main/pytorch_model.bin
145 MB
- Xet hash:
- 6cbaed3cd462a53839b7fa9537ee2eebc35edeeae89fd95e653a39b162d9c192
- Size of remote file:
- 145 MB
- SHA256:
- e26d7b654f3b5e45e4d9e6666dabfa6bcbe1232401bfcdb51e62ad22ad782d17
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