Added model card
Browse files
README.md
ADDED
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
pipeline_tag: sentence-similarity
|
4 |
+
---
|
5 |
+
|
6 |
+
ONNX port of [thenlper/gte-large](https://huggingface.co/thenlper/gte-large) text classification and similarity searches.
|
7 |
+
|
8 |
+
### Usage
|
9 |
+
|
10 |
+
Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
|
11 |
+
|
12 |
+
```py
|
13 |
+
from fastembed import TextEmbedding
|
14 |
+
|
15 |
+
documents = [
|
16 |
+
"You should stay, study and sprint.",
|
17 |
+
"History can only prepare us to be surprised yet again.",
|
18 |
+
]
|
19 |
+
|
20 |
+
model = TextEmbedding(model_name="thenlper/gte-large")
|
21 |
+
embeddings = list(model.embed(documents))
|
22 |
+
|
23 |
+
# [
|
24 |
+
# array([
|
25 |
+
# 0.00611658, 0.00068912, -0.0203846, ..., -0.01751488, -0.01174267,
|
26 |
+
# 0.01463472
|
27 |
+
# ],
|
28 |
+
# dtype=float32),
|
29 |
+
# array([
|
30 |
+
# 0.00173448, -0.00329958, 0.01557874, ..., -0.01473586, 0.0281806,
|
31 |
+
# -0.00448205
|
32 |
+
# ],
|
33 |
+
# dtype=float32)
|
34 |
+
# ]
|
35 |
+
```
|