Text-to-Speech
Transformers
Safetensors
moss_tts_local
feature-extraction
voice-cloning
custom_code
moss-tts
moss-tts-local
Instructions to use ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5: direct link, hf CLI and curl.
- Browser
- Download file 254 Bytes
-
https://huggingface.co/ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5/resolve/main/__init__.py
- Command line
-
hf download hf://ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5/__init__.py
-
curl -L -o __init__.py https://huggingface.co/ArchiveStudio/MOSS-TTS-Local-Transformer-v1.5/resolve/main/__init__.py
254 Bytes
| from .configuration_moss_tts import MossTTSLocalConfig | |
| from .modeling_moss_tts import MossTTSLocalModel | |
| from .processing_moss_tts import MossTTSLocalProcessor | |
| __all__ = [ | |
| "MossTTSLocalConfig", | |
| "MossTTSLocalModel", | |
| "MossTTSLocalProcessor", | |
| ] | |