Instructions to use crocutacrocuto/dinov2-large-MEG7-20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crocutacrocuto/dinov2-large-MEG7-20 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="crocutacrocuto/dinov2-large-MEG7-20") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("crocutacrocuto/dinov2-large-MEG7-20") model = AutoModelForImageClassification.from_pretrained("crocutacrocuto/dinov2-large-MEG7-20") - Notebooks
- Google Colab
- Kaggle
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pipeline_tag: image-classification
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base_model:
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pipeline_tag: image-classification
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base_model:
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- facebook/dinov2-large
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metrics:
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- accuracy
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library_name: transformers
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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