Instructions to use hf-tiny-model-private/tiny-random-YolosModel 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-YolosModel 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-YolosModel", device_map="auto")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-YolosModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-YolosModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12c2e4631c638fafcc6cebe1b473cf2e2e5855f2e0c3614605ecde8cb3bc2f44
- Size of remote file:
- 304 kB
- SHA256:
- 9fc96b6edfd8a1156a1e25f1bed687d4dce4b0f61dc67c3468cd180332470586
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