Instructions to use hf-tiny-model-private/tiny-random-DeiTModel 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-DeiTModel 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-DeiTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DeiTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DeiTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f3306924f3f25b29c4f861b57a2a5900cff23e1ea42874686cc4ab4261719fb
- Size of remote file:
- 292 kB
- SHA256:
- 03a32e51680064682ec14fb6dfc543e6d743657da3153b2418100c81a84124c8
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