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:
- ff1ff73488d426dd423cc395a10065628e15fa1bccb55b09710ff6796de71c4d
- Size of remote file:
- 20 kB
- SHA256:
- d860a933d31cda9c8b2220384545b2e7c9e022e8456769326dcb5cfe34f3b5b6
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