Instructions to use hf-internal-testing/tiny-random-DacModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DacModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DacModel")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-DacModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DacModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b93f528d4633a24510966a54f9f7f2c54f1f5f6c90e55b1a4e0ffb1ba67fc69b
- Size of remote file:
- 295 kB
- SHA256:
- 0f1358b662151d8cd279fdd3a77612eaf5339206a9dc81119e4891539fd1f6e1
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