unicom-vit-b-32 model card

README.md

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+---
+license: apache-2.0
+pipeline_tag: image-feature-extraction
+---
+
+ONNX port of [Unicom](https://arxiv.org/abs/2304.05884) model from [open-metric-learning](https://github.com/OML-Team/open-metric-learning).
+
+This model is intended to be used for similarity search.
+
+### Usage
+
+Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
+
+```py
+from fastembed import ImageEmbedding
+
+images = [
+    "./path/to/image1.jpg",
+    "./path/to/image2.jpg",
+]
+
+model = ImageEmbedding(model_name="Qdrant/Unicom-ViT-B-32")
+embeddings = list(model.embed(images))
+
+# [
+#   array([ 0.04177791,  0.0550059 ,  0.00025418,  0.0252876 , ..., dtype=float32),
+#   array([2.23932182e-03,  4.68995124e-02,  3.28772422e-03,  7.57176951e-02, ...], dtype=float32)
+# ]
+```