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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6eeaceb2bc53c9b5191e290139cdc2d44c0dc873e393161cb87687f60ababdef
- Size of remote file:
- 103 MB
- SHA256:
- 0397c68e2d922d972d801c9a4bc1b9d9b050c913aaf8da6c72498a8b2be8208b
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