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:
- 4a2b7983246a97ac9836ac9d57694e798fb75d14b20f79c08eb43938ce31ff67
- Size of remote file:
- 4.83 MB
- SHA256:
- fa4aa52905fc8ea30b77ff7e9f045225a3d48139fd156f1efc5ab5b67479b3c6
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