Update README.md

README.md

@@ -1,7 +1,5 @@
 ---
 license: mit
----
----
 pipeline_tag: sentence-similarity
 tags:
 - sentence-transformers
@@ -14,7 +12,7 @@ tags:
 
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
-<!--- Describe your model here -->
+Base on BAAI/bge-m3, finetuned with financial data
 
 ## Usage (Sentence-Transformers)
 
@@ -30,7 +28,7 @@ Then you can use the model like this:
 from sentence_transformers import SentenceTransformer
 sentences = ["This is an example sentence", "Each sentence is converted"]
 
-model = SentenceTransformer('{MODEL_NAME}')
+model = SentenceTransformer('liuxiong332/bge-m3-financial-mixed')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```
@@ -39,7 +37,6 @@ print(embeddings)
 
 ## Evaluation Results
 
-<!--- Describe how your model was evaluated -->
 
 For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME})
 
@@ -54,6 +51,3 @@ SentenceTransformer(
 )
 ```
 
-## Citing & Authors
-
-<!--- Describe where people can find more information -->