Text-to-Speech
Transformers
Safetensors
moss_tts_local
feature-extraction
voice-cloning
custom_code
moss-tts
moss-tts-local
Instructions to use Jinstudio/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 Jinstudio/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="Jinstudio/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("Jinstudio/MOSS-TTS-Local-Transformer-v1.5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from Jinstudio/MOSS-TTS-Local-Transformer-v1.5: direct link, hf CLI and curl.
- Browser
- Download file 210 Bytes
-
https://huggingface.co/Jinstudio/MOSS-TTS-Local-Transformer-v1.5/resolve/main/processor_config.json
- Command line
-
hf download hf://Jinstudio/MOSS-TTS-Local-Transformer-v1.5/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/Jinstudio/MOSS-TTS-Local-Transformer-v1.5/resolve/main/processor_config.json
210 Bytes
| { | |
| "processor_class": "MossTTSLocalProcessor", | |
| "audio_tokenizer_name_or_path": "OpenMOSS-Team/MOSS-Audio-Tokenizer-v2", | |
| "auto_map": { | |
| "AutoProcessor": "processing_moss_tts.MossTTSLocalProcessor" | |
| } | |
| } | |