Instructions to use KauPage/speecht5_tts_SVM_mr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KauPage/speecht5_tts_SVM_mr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="KauPage/speecht5_tts_SVM_mr")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("KauPage/speecht5_tts_SVM_mr") model = AutoModelForTextToSpectrogram.from_pretrained("KauPage/speecht5_tts_SVM_mr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KauPage/speecht5_tts_SVM_mr: direct link, hf CLI and curl.
- Browser
- Download file 585 MB
-
https://huggingface.co/KauPage/speecht5_tts_SVM_mr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KauPage/speecht5_tts_SVM_mr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KauPage/speecht5_tts_SVM_mr/resolve/main/pytorch_model.bin
585 MB
- Xet hash:
- 1d5df202c09ac63fd38fcc22a53ecc3f11739d36d714e7a262bd7d8316b01a47
- Size of remote file:
- 585 MB
- SHA256:
- 13758c1553756334f1fd162de1b9057f3fa5bab9109473a696ef788c2e79fc84
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