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unicom-vit-b-32 model card (#1)
Browse files- unicom-vit-b-32 model card (9f48f41968f74ee944d8add3618e194d7b4e8176)
Co-authored-by: George <jmzzomg@users.noreply.huggingface.co>
README.md
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---
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license: apache-2.0
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pipeline_tag: image-feature-extraction
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---
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ONNX port of [Unicom](https://arxiv.org/abs/2304.05884) model from [open-metric-learning](https://github.com/OML-Team/open-metric-learning).
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This model is intended to be used for similarity search.
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### Usage
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Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
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```py
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from fastembed import ImageEmbedding
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images = [
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"./path/to/image1.jpg",
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"./path/to/image2.jpg",
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]
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model = ImageEmbedding(model_name="Qdrant/Unicom-ViT-B-32")
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embeddings = list(model.embed(images))
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# [
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# array([ 0.04177791, 0.0550059 , 0.00025418, 0.0252876 , ..., dtype=float32),
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# array([2.23932182e-03, 4.68995124e-02, 3.28772422e-03, 7.57176951e-02, ...], dtype=float32)
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# ]
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```
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