Update README.md

README.md

@@ -12,8 +12,8 @@ tags:
 # {MODEL_NAME}
 
 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.
+Was trained using the multiple negative ranking loss technique with the MsMarco data set translated into Spanish based on the Beto model (Spanish Bert Cased).
 
-<!--- Describe your model here -->
 
 ## Usage (Sentence-Transformers)
 
@@ -29,7 +29,7 @@ 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('emersoftware/beto-st-mnrl-msmarco-es')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```