Instructions to use hf-tiny-model-private/tiny-random-DinatModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DinatModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-DinatModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DinatModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DinatModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 407a2186507e8d85e1416eeaf5ebc49cb9f3e1c040724cadaf7737fac155afd0
- Size of remote file:
- 321 kB
- SHA256:
- a8417cc22dcd9c89263565ce8a64779bbc25929eca37eaac54b82838bf18d27b
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