Update README.md
Browse files
README.md
CHANGED
@@ -7,21 +7,14 @@ tags:
|
|
7 |
|
8 |
---
|
9 |
|
10 |
-
#
|
11 |
|
12 |
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
|
13 |
|
14 |
<!--- Describe your model here -->
|
15 |
|
16 |
-
## Usage
|
17 |
|
18 |
-
Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
|
19 |
-
|
20 |
-
```
|
21 |
-
pip install -U sentence-transformers
|
22 |
-
```
|
23 |
-
|
24 |
-
Then you can use the model like this:
|
25 |
|
26 |
```python
|
27 |
embedding_latex = model.encode([{'latex': latex}])
|
@@ -45,6 +38,7 @@ SentenceTransformer(
|
|
45 |
## Citing & Authors
|
46 |
|
47 |
<!--- Describe where people can find more information -->
|
|
|
48 |
@inproceedings{wang2023math,
|
49 |
title={Math Information Retrieval with Contrastive Learning of Formula Embeddings},
|
50 |
author={Wang, Jingyi and Tian, Xuedong},
|
|
|
7 |
|
8 |
---
|
9 |
|
10 |
+
# CLFE(ConMath)
|
11 |
|
12 |
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
|
13 |
|
14 |
<!--- Describe your model here -->
|
15 |
|
16 |
+
## Usage
|
17 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
18 |
|
19 |
```python
|
20 |
embedding_latex = model.encode([{'latex': latex}])
|
|
|
38 |
## Citing & Authors
|
39 |
|
40 |
<!--- Describe where people can find more information -->
|
41 |
+
|
42 |
@inproceedings{wang2023math,
|
43 |
title={Math Information Retrieval with Contrastive Learning of Formula Embeddings},
|
44 |
author={Wang, Jingyi and Tian, Xuedong},
|