Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
pipeline_tag: image-classification
|
4 |
+
---
|
5 |
+
|
6 |
+
ONNX port of [sentence-transformers/clip-ViT-B-32](https://huggingface.co/sentence-transformers/clip-ViT-B-32).
|
7 |
+
|
8 |
+
This model is intended to be used for image classification and similarity searches.
|
9 |
+
|
10 |
+
### Usage
|
11 |
+
|
12 |
+
Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
|
13 |
+
|
14 |
+
```py
|
15 |
+
from fastembed import ImageEmbedding
|
16 |
+
|
17 |
+
images = [
|
18 |
+
"./path/to/image1.jpg",
|
19 |
+
"./path/to/image2.jpg",
|
20 |
+
]
|
21 |
+
|
22 |
+
model = ImageEmbedding(model_name="Qdrant/clip-ViT-B-32-vision")
|
23 |
+
embeddings = list(embedding_model.embed(images))
|
24 |
+
|
25 |
+
# [
|
26 |
+
# array([-0.1115, 0.0097, 0.0052, 0.0195, ...], dtype=float32),
|
27 |
+
# array([-0.1019, 0.0635, -0.0332, 0.0522, ...], dtype=float32)
|
28 |
+
# ]
|
29 |
+
```
|