Text-to-Speech
Transformers
Safetensors
Basque
arktts
feature-extraction
tts
basque
euskara
audio
audio8
fine-tuned
custom_code
Instructions to use itzune/zortzi-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itzune/zortzi-tts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="itzune/zortzi-tts", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("itzune/zortzi-tts", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab939bfbfdde24485101aa13a1a2e24c0e3b726c521815739e99780b5d0942c3
- Size of remote file:
- 12.2 MB
- SHA256:
- f24e08099d45a8adf3f52f5f0b03276e433bb9d689bb15fcbcc48ce58744588b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.