Instructions to use hf-internal-testing/tiny-random-BeitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BeitModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-BeitModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-BeitModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-BeitModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c9fa67a86bb8cb852deca323d7afec3a3b21e3beae2d3b788c1a779b24f4790
- Size of remote file:
- 119 kB
- SHA256:
- e7442b97e45612667afce70a75e63c5516300f8208d4fefa9084cc314dd64922
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