Instructions to use hf-tiny-model-private/tiny-random-GroupViTModel 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-GroupViTModel 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-GroupViTModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-GroupViTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GroupViTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75f3b03586007d19db3913f93540470fac83aac762249b6db4e3a607b971fc55
- Size of remote file:
- 4.31 MB
- SHA256:
- 5419e0e98ee8ec46ebb1c14eda54fe77cd9170edf3b2a0b295ae5e9e169ec4ae
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