Instructions to use facebook/ijepa_vitg16_22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/ijepa_vitg16_22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/ijepa_vitg16_22k")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/ijepa_vitg16_22k") model = AutoModel.from_pretrained("facebook/ijepa_vitg16_22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c6c6943d0c7bc61e1f3820b195815e368d06fcd4d65d86a2e76ce43eb2bd92c
- Size of remote file:
- 4.05 GB
- SHA256:
- 1eb25fdbbcbac89bce19da8ba74f677b6388864af934e470799f71ca3433ff3e
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