Instructions to use ovieyra21/tt-mbm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ovieyra21/tt-mbm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ovieyra21/tt-mbm")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("ovieyra21/tt-mbm") model = AutoModelForTextToSpectrogram.from_pretrained("ovieyra21/tt-mbm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from ovieyra21/tt-mbm: direct link, hf CLI and curl.
- Browser
- Download file 1.16 GB
-
https://huggingface.co/ovieyra21/tt-mbm/resolve/main/optimizer.pt
- Command line
-
hf download hf://ovieyra21/tt-mbm/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ovieyra21/tt-mbm/resolve/main/optimizer.pt
1.16 GB
- Xet hash:
- 7e67c32ffb5f4b7a2caa74bd05955bda4a4d454351688a601ceaf7cedc8fe8ac
- Size of remote file:
- 1.16 GB
- SHA256:
- 07465a555b92f42d646060f915c82147b9778577d2756ac9666c94563bf25d65
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