Instructions to use hf-tiny-model-private/tiny-random-ConditionalDetrModel 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-ConditionalDetrModel 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-ConditionalDetrModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ConditionalDetrModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ConditionalDetrModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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