Text-to-Speech
Transformers
ONNX
Safetensors
lingv3_tts
feature-extraction
audio
voice-cloning
multilingual
mixture-of-experts
speech-generation
custom_code
Instructions to use inclusionAI/Ming-3.0-tts-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/Ming-3.0-tts-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="inclusionAI/Ming-3.0-tts-tiny", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inclusionAI/Ming-3.0-tts-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download configuration_audio_vae.py from inclusionAI/Ming-3.0-tts-tiny: direct link, hf CLI and curl.
- Browser
- Download file 1.18 kB
-
https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny/resolve/main/configuration_audio_vae.py
- Command line
-
hf download hf://inclusionAI/Ming-3.0-tts-tiny/configuration_audio_vae.py
-
curl -L -o configuration_audio_vae.py https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny/resolve/main/configuration_audio_vae.py
1.18 kB
| from transformers import PretrainedConfig | |
| class AudioVAEconfig(PretrainedConfig): | |
| def __init__( | |
| self, | |
| sample_rate: int=16000, | |
| enc_kwargs: dict = None, | |
| semantic_module_kwargs: dict = None, | |
| dec_kwargs: dict = None, | |
| hifi_gan_disc_kwargs: dict = None, | |
| spec_disc_kwargs: dict = None, | |
| lambda_disc=1.0, | |
| lambda_mel_loss=15, | |
| lambda_adv=1.0, | |
| lambda_feat_match_loss=1.0, | |
| lambda_semantic=5.0, | |
| init_method='normal', | |
| patch_size=-1, | |
| **kwargs | |
| ): | |
| self.sample_rate = sample_rate | |
| self.enc_kwargs = enc_kwargs | |
| self.semantic_module_kwargs = semantic_module_kwargs | |
| self.dec_kwargs = dec_kwargs | |
| self.hifi_gan_disc_kwargs = hifi_gan_disc_kwargs | |
| self.spec_disc_kwargs = spec_disc_kwargs | |
| self.lambda_disc = lambda_disc | |
| self.lambda_mel_loss = lambda_mel_loss | |
| self.lambda_adv = lambda_adv | |
| self.lambda_feat_match_loss = lambda_feat_match_loss | |
| self.lambda_semantic = lambda_semantic | |
| self.init_method = init_method | |
| self.patch_size = patch_size | |
| super().__init__(**kwargs) | |