Instructions to use hf-tiny-model-private/tiny-random-CvtModel 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-CvtModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-CvtModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-CvtModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-CvtModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46bd5dd4c14bab28a9142bb566bd807ef729db867a9fa7da5281cc193e80c8df
- Size of remote file:
- 5.25 MB
- SHA256:
- 41ec609fe8c4d191bc6e6408069f09fec8392753321204859b908267b79da9d6
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