Text-to-Speech
Transformers
Safetensors
hifi_gan
feature-extraction
audio
vocoder
hifi-gan
bigvgan
neural-vocoder
speaker-conditioning
audio-watermarking
custom_code
Instructions to use mlr2000/vocoder-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlr2000/vocoder-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="mlr2000/vocoder-small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlr2000/vocoder-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 183 Bytes
1fdc661 | 1 2 3 4 5 | from .configuration_hifigan import HiFiGANConfig
from .modeling_hifigan import HiFiGANArchitecture, HiFiGANOutput
__all__ = ["HiFiGANConfig", "HiFiGANArchitecture", "HiFiGANOutput"]
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