Instructions to use hf-tiny-model-private/tiny-random-DetrModel 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-DetrModel 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-DetrModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DetrModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DetrModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e78610762044460469132b0c1be1dad2250c8b1b6eca49b0e5cabba91ab02ff
- Size of remote file:
- 103 MB
- SHA256:
- 83aed283b1748985617a5f44ee03d8868b91ba5d76fb5b117e8eaed0e9060a34
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