Instructions to use hf-internal-testing/tiny-random-ConditionalDetrModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConditionalDetrModel 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-ConditionalDetrModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ConditionalDetrModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ConditionalDetrModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 336ae541a842fb9c2f1bd0818c5276d424063f498f3333fc0d439123157543f4
- Size of remote file:
- 106 MB
- SHA256:
- e0e094eacb58382a0dbd17cef2d2054da1024cbc96a831958157033b623a2f8e
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