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:
- 94a640b7fc0f3b974fde9652a1ff84ad28fae3016f783aa38638cbf70ba58614
- Size of remote file:
- 1.89 kB
- SHA256:
- 04fd39ae31c48ce4c2578d25e07f436b671fa900fd526de06d68054735fe4fc6
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