Instructions to use AdaCodruta/speecht5_finetuned_ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdaCodruta/speecht5_finetuned_ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="AdaCodruta/speecht5_finetuned_ro")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("AdaCodruta/speecht5_finetuned_ro") model = AutoModelForTextToSpectrogram.from_pretrained("AdaCodruta/speecht5_finetuned_ro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AdaCodruta/speecht5_finetuned_ro: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/AdaCodruta/speecht5_finetuned_ro/resolve/main/training_args.bin
- Command line
-
hf download hf://AdaCodruta/speecht5_finetuned_ro/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AdaCodruta/speecht5_finetuned_ro/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- f39b84ef1490b2395e5d6701cb56df4807c86fa458f5a3c34e1a54f68c1d31f2
- Size of remote file:
- 5.5 kB
- SHA256:
- 7bac05a338c2c253f49d2c688ec6320aabb64988d32e3a46b6067c743aae974a
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