Instructions to use facebook/ijepa_vith14_22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/ijepa_vith14_22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/ijepa_vith14_22k")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/ijepa_vith14_22k") model = AutoModel.from_pretrained("facebook/ijepa_vith14_22k") - Notebooks
- Google Colab
- Kaggle
Update README.md
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by qubvel-hf - opened
README.md
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@@ -45,7 +45,7 @@ url_2 = "http://images.cocodataset.org/val2017/000000219578.jpg"
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image_1 = Image.open(requests.get(url_1, stream=True).raw)
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image_2 = Image.open(requests.get(url_2, stream=True).raw)
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model_id = "
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processor = AutoProcessor.from_pretrained(model_id)
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model = AutoModel.from_pretrained(model_id)
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image_1 = Image.open(requests.get(url_1, stream=True).raw)
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image_2 = Image.open(requests.get(url_2, stream=True).raw)
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model_id = "facebook/ijepa_vith14_22k"
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processor = AutoProcessor.from_pretrained(model_id)
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model = AutoModel.from_pretrained(model_id)
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