Instructions to use awkyu/audiogen-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use awkyu/audiogen-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="awkyu/audiogen-medium")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("awkyu/audiogen-medium") model = AutoModelForTextToWaveform.from_pretrained("awkyu/audiogen-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95190f5ac4312d06a7dade654db36f55fa4009304ee085024d76cae727f08ba1
- Size of remote file:
- 3.68 GB
- SHA256:
- f3b20997834de1ca47d6a31d00a5dc37019b279c7c8f250fd482d56def04faaa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.