Instructions to use kfahn/speecht5_finetuned_voxpopuli_cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kfahn/speecht5_finetuned_voxpopuli_cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="kfahn/speecht5_finetuned_voxpopuli_cs")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("kfahn/speecht5_finetuned_voxpopuli_cs") model = AutoModelForTextToSpectrogram.from_pretrained("kfahn/speecht5_finetuned_voxpopuli_cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kfahn/speecht5_finetuned_voxpopuli_cs: direct link, hf CLI and curl.
- Browser
- Download file 578 MB
-
https://huggingface.co/kfahn/speecht5_finetuned_voxpopuli_cs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kfahn/speecht5_finetuned_voxpopuli_cs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kfahn/speecht5_finetuned_voxpopuli_cs/resolve/main/pytorch_model.bin
578 MB
- Xet hash:
- 11d7ca6fe54274685637956927fb090e5c86a842338d2485a3ddbce954e3ef53
- Size of remote file:
- 578 MB
- SHA256:
- f5e32969983f780980da67d2f4a8acc0705b5010bdb4c82464eb093c10f6804f
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