Text-to-Speech
Transformers
Safetensors
moss_tts_local
feature-extraction
podcast
multi-speaker
voice-cloning
expressive-speech
custom-code
research
custom_code
Instructions to use laion/Humanness-Voice-Podcast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laion/Humanness-Voice-Podcast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="laion/Humanness-Voice-Podcast", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("laion/Humanness-Voice-Podcast", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from laion/Humanness-Voice-Podcast: direct link, hf CLI and curl.
- Browser
- Download file 209 Bytes
-
https://huggingface.co/laion/Humanness-Voice-Podcast/resolve/main/processor_config.json
- Command line
-
hf download hf://laion/Humanness-Voice-Podcast/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/laion/Humanness-Voice-Podcast/resolve/main/processor_config.json
209 Bytes
| { | |
| "processor_class": "MossTTSLocalProcessor", | |
| "auto_map": { | |
| "AutoProcessor": "processing_moss_tts.MossTTSLocalProcessor" | |
| }, | |
| "audio_tokenizer_name_or_path": "OpenMOSS-Team/MOSS-Audio-Tokenizer-v2" | |
| } |