Instructions to use hf-internal-testing/tiny-random-IdeficsModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IdeficsModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-IdeficsModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-IdeficsModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-IdeficsModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 216487209203839f238f9b9adcc4aa9d99ed9687d63274ce80ab963e11827942
- Size of remote file:
- 4.59 MB
- SHA256:
- d16582690a33438bbbe8edfd379882046b9765a3777dff532c8e5f5a8713bcea
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