Readme

app.py

@@ -15,9 +15,11 @@ menu = st.sidebar.radio("", options=["Contributions & Evaluation", "Sentence Sim
 
 st.markdown('''
 
-Sentence Transformers is a set of Frameworks & Models that are trained to generate Sentence Embeddings. Generated 
-Sentence Embeddings can be used for Sentence Simliarity / Asymmetric QA / Semantic Search / Clustering among other tasks.
-We trained multiple general-purpose flax-sentence-embeddings models starting from different BERT models including 
+**Sentence Transformers** is a set of frameworks & models that are trained to generate Embeddings from input sentences. 
+Generated Sentence Embeddings can be used for Sentence Simliarity / Asymmetric QA / Semantic Search / Clustering
+among other tasks.
+
+We trained multiple general-purpose Sentence Transformers models based on different LMs including 
 distilroberta, mpnet and MiniLM-l6. They were trained using Siamese network configuration with custom **Contrastive Loss** 
 inspired by OpenAI CLIP. The models were trained on a dataset comprising of [1 Billion+ training corpus](https://huggingface.co/flax-sentence-embeddings/all_datasets_v4_MiniLM-L6#training-data) with the v3 setup.