Unicom-ViT-B-16 / README.md
generall93's picture
add model card for unicom-vit-b-16 (#1)
65220d6 verified
|
raw
history blame
804 Bytes
---
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-16")
embeddings = list(model.embed(images))
# [
# array([ 1.70463976e-02, -3.60863991e-02, 1.24569749e-02, -4.28437591e-02 , ...], dtype=float32),
# array([ 0.03675087, 0.00696867, -0.01495106, -0.02828627, ...], dtype=float32)
# ]
```