Text-to-Speech
Transformers
Safetensors
English
moss_tts_nano
feature-extraction
tts
moss-tts-nano
indian-english
lora
voice-cloning
custom_code
Instructions to use IOTEverythin/roxi-tts-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IOTEverythin/roxi-tts-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="IOTEverythin/roxi-tts-v2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IOTEverythin/roxi-tts-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05fc9717a81622b6de868db6d15b9193841ab60e37a560cf893c570896124c11
- Size of remote file:
- 471 kB
- SHA256:
- c353ee1479b536bf414c1b247f5542b6607fb8ae91320e5af1781fee200fddff
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