Update README.md
Browse files
README.md
CHANGED
@@ -9,9 +9,9 @@ pipeline_tag: sentence-similarity
|
|
9 |
license: apache-2.0
|
10 |
---
|
11 |
|
12 |
-
# MizoEmbed
|
13 |
|
14 |
-
MizoEmbed
|
15 |
|
16 |
The model maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
|
17 |
|
@@ -41,7 +41,7 @@ Then you can load this model and run inference.
|
|
41 |
from sentence_transformers import SentenceTransformer
|
42 |
|
43 |
# Download from the 🤗 Hub
|
44 |
-
model = SentenceTransformer("sarkii/MizoEmbed")
|
45 |
# Run inference
|
46 |
sentences = [
|
47 |
'Nepal a ka zin chu ka hlawkpui hle mai. Nupui te pawh ka hmu tep e.',
|
|
|
9 |
license: apache-2.0
|
10 |
---
|
11 |
|
12 |
+
# MizoEmbed-1
|
13 |
|
14 |
+
MizoEmbed-1 is the first dense embedding model developed specifically for the Mizo language. This pioneering model provides vector representations of Mizo text, enabling various natural language processing tasks and applications for the underrepresented language.
|
15 |
|
16 |
The model maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
|
17 |
|
|
|
41 |
from sentence_transformers import SentenceTransformer
|
42 |
|
43 |
# Download from the 🤗 Hub
|
44 |
+
model = SentenceTransformer("sarkii/MizoEmbed-1")
|
45 |
# Run inference
|
46 |
sentences = [
|
47 |
'Nepal a ka zin chu ka hlawkpui hle mai. Nupui te pawh ka hmu tep e.',
|