Instructions to use hf-internal-testing/tiny-random-BarkModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BarkModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-BarkModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-BarkModel") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-BarkModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-BarkModel: direct link, hf CLI and curl.
- Browser
- Download file 937 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-BarkModel/resolve/refs%2Fpr%2F3/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BarkModel@refs/pr/3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-BarkModel/resolve/refs%2Fpr%2F3/pytorch_model.bin
937 kB
- Xet hash:
- 316cbbce629e7f6544cd512bc2e4d030bea5e34c0e0f3137ca61276a93e7510c
- Size of remote file:
- 937 kB
- SHA256:
- 04c86d56673e789ed0f4fd2d6ef685d43fcdead13e862bff2f7f980437da72af
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