Text-to-Speech
Transformers
Safetensors
Persian
arktts
feature-extraction
tts
persian
farsi
voice-cloning
audio8
custom_code
Instructions to use ArminRahimi/Audio8-TTS-Persian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArminRahimi/Audio8-TTS-Persian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ArminRahimi/Audio8-TTS-Persian", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArminRahimi/Audio8-TTS-Persian", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download codec.pth from ArminRahimi/Audio8-TTS-Persian: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/ArminRahimi/Audio8-TTS-Persian/resolve/main/codec.pth
- Command line
-
hf download hf://ArminRahimi/Audio8-TTS-Persian/codec.pth
-
curl -L -o codec.pth https://huggingface.co/ArminRahimi/Audio8-TTS-Persian/resolve/main/codec.pth
1.35 GB
- Xet hash:
- 19fb75433d777a145db9a19368826ed88cd82ca183faeb2fc14e41bdcd09c2c2
- Size of remote file:
- 1.35 GB
- SHA256:
- c310505aa11fe2f6cc63b8d3130dc7e77e73227774f5c62575769b1f47a8d048
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.