Instructions to use froabera/speecht5_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use froabera/speecht5_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="froabera/speecht5_finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("froabera/speecht5_finetuned") model = AutoModelForTextToSpectrogram.from_pretrained("froabera/speecht5_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from froabera/speecht5_finetuned: direct link, hf CLI and curl.
- Browser
- Download file 5.39 kB
-
https://huggingface.co/froabera/speecht5_finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://froabera/speecht5_finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/froabera/speecht5_finetuned/resolve/main/training_args.bin
5.39 kB
- Xet hash:
- aaba0abc5ed2bb32f88ffe5b3f404efc70cbe87104c7889f1c2012f2859853a8
- Size of remote file:
- 5.39 kB
- SHA256:
- 78132a3bd5c7a72fabd9098ddd1c0c6d95e6fff5ea1b32ca2639ea32698d06a0
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