Instructions to use hf-internal-testing/tiny-random-CvtModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CvtModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-CvtModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-CvtModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-CvtModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d543fd6db03976b98d8a16cc3b4ed0bf286ea3eab4c032c2a8a84d00229f7456
- Size of remote file:
- 5.66 MB
- SHA256:
- e40dc4f1cc37a84f406cbaba3b6623ac7da5819631d7cac2500f35ceb6a36a3b
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