Instructions to use abdelkader12/Text_To_Speech_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdelkader12/Text_To_Speech_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="abdelkader12/Text_To_Speech_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("abdelkader12/Text_To_Speech_model") model = AutoModelForTextToSpectrogram.from_pretrained("abdelkader12/Text_To_Speech_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from abdelkader12/Text_To_Speech_model: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/abdelkader12/Text_To_Speech_model/resolve/main/training_args.bin
- Command line
-
hf download hf://abdelkader12/Text_To_Speech_model/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/abdelkader12/Text_To_Speech_model/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 5e40e54ec4c05d7aff37843413a7c9fe2193f2c63cf3fd4b81f9047d208dee1a
- Size of remote file:
- 5.37 kB
- SHA256:
- c9219e97150c5c1c981e1e78376294866980b7753dc4a33a1a5060767d0adf25
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