Instructions to use artificial-feelings/bark-forked with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artificial-feelings/bark-forked with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="artificial-feelings/bark-forked")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("artificial-feelings/bark-forked") model = AutoModelForTextToWaveform.from_pretrained("artificial-feelings/bark-forked", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8c15b401ffdad785befa02847abce08818a959e8dd8df347d501c70c3aba21a
- Size of remote file:
- 2.17 kB
- SHA256:
- a7e818c23cd631d65219175351f9630f2d90d09a1fb261e0059ad91da85c9a96
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