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 training_args.bin from KauPage/speecht5_tts_SVM_mr: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/KauPage/speecht5_tts_SVM_mr/resolve/main/training_args.bin
- Command line
-
hf download hf://KauPage/speecht5_tts_SVM_mr/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/KauPage/speecht5_tts_SVM_mr/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 60295af2b95aa39652e50af762d9bbe944039520d33ec8b5571ab1e070e58362
- Size of remote file:
- 4.09 kB
- SHA256:
- fe3c5ad7845ac6db4246ed3c20414c09c4f92922740a5d75bf3db042f1073041
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