Instructions to use ylacombe/bark-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ylacombe/bark-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="ylacombe/bark-large")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("ylacombe/bark-large") model = AutoModelForTextToWaveform.from_pretrained("ylacombe/bark-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc326f4fafff05f8cdb76f50c5aba2aaa8882effbe2de5560802b598632b5fcd
- Size of remote file:
- 12.4 kB
- SHA256:
- a7be1f0a435798a9aaf94b796c0e4008194397b798e410630ce3e2abf0468750
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