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:
- d675bbfcbf59850e9e0a1547ac96fecfff06ebd6028aa17f15c8965359887254
- Size of remote file:
- 35.3 kB
- SHA256:
- 6e97d71d8a7120bff91f08ccf1d0e6d1e8b6983642d56dad0cbe0f8dc2554343
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