Instructions to use mikhail-panzo/dutch_example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikhail-panzo/dutch_example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="mikhail-panzo/dutch_example")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("mikhail-panzo/dutch_example") model = AutoModelForTextToSpectrogram.from_pretrained("mikhail-panzo/dutch_example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mikhail-panzo/dutch_example: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/mikhail-panzo/dutch_example/resolve/main/training_args.bin
- Command line
-
hf download hf://mikhail-panzo/dutch_example/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mikhail-panzo/dutch_example/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- e5e25a7c3cd5d2f078c914a78dce4229e8e4a5276e2d53ca8d3dff0767e76df6
- Size of remote file:
- 5.11 kB
- SHA256:
- d0128bd443458305b92101e667bfff44abcf3c39177e7d9cebb80a018154dcc4
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