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%2F1/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BarkModel@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-BarkModel/resolve/refs%2Fpr%2F1/pytorch_model.bin
937 kB
- Xet hash:
- 325e1b58a877513d212a7db9958848dca9bfb0123de77d35ce7fa14c2ec44a05
- Size of remote file:
- 937 kB
- SHA256:
- 65b6987484c1e8d0f85c91e8352678d6ae663eb346dcf0b800898d3e4cfbd31c
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