Update README.md

README.md

@@ -4,15 +4,22 @@ tags:
 - sentence-transformers
 - feature-extraction
 - sentence-similarity
+language:
+- ru
+- en
+base_model: sentence-transformers/LaBSE
+inference: false
 
 ---
 
-# {MODEL_NAME}
+# LaBSE_geonames_RU_RELOCATION
 
 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.
 
 <!--- Describe your model here -->
 
+This model fine tuned on geonames cities15000 in RU and popular relocation countries.
+
 ## Usage (Sentence-Transformers)
 
 Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
@@ -25,22 +32,15 @@ Then you can use the model like this:
 
 ```python
 from sentence_transformers import SentenceTransformer
-sentences = ["This is an example sentence", "Each sentence is converted"]
+cities = ["Vladivostok", "Moscow"]
 
-model = SentenceTransformer('{MODEL_NAME}')
-embeddings = model.encode(sentences)
+model = SentenceTransformer('artefucktor/LaBSE_geonames_RU_RELOCATION')
+embeddings = model.encode(cities)
 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})
-
-
 ## Training
 The model was trained with the parameters: