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:
- e275bb571442fdf2bb294b1b2c1367c4ff9176a4d8e4f157827d8e9020ee1b55
- Size of remote file:
- 5.01 MB
- SHA256:
- 2414cb62447af542ea8baf7de64d3a4e930c9fb7819a1632839274cbeea9d7ba
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