Instructions to use RamWithAPlan/speecht5_tts_voxpopuli_nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RamWithAPlan/speecht5_tts_voxpopuli_nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="RamWithAPlan/speecht5_tts_voxpopuli_nl")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("RamWithAPlan/speecht5_tts_voxpopuli_nl") model = AutoModelForTextToSpectrogram.from_pretrained("RamWithAPlan/speecht5_tts_voxpopuli_nl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RamWithAPlan/speecht5_tts_voxpopuli_nl: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/RamWithAPlan/speecht5_tts_voxpopuli_nl/resolve/main/training_args.bin
- Command line
-
hf download hf://RamWithAPlan/speecht5_tts_voxpopuli_nl/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RamWithAPlan/speecht5_tts_voxpopuli_nl/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- f70c2b85f837e3a758f9de32580cf0e9c9a28f533cdb0629dc0f6be2e1911c6f
- Size of remote file:
- 4.16 kB
- SHA256:
- 1fd286aa5aae30b205313630363eb7d32e95d8cd17a4719249fe7866ee68c9fc
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