Update README.md

README.md

@@ -12,7 +12,7 @@ pipeline_tag: sentence-similarity
 
 # Model Card for nasa-smd-ibm-st-v2
 
-`nasa-smd-ibm-st-v2` is a Bi-encoder sentence transformer model, that is fine-tuned from nasa-smd-ibm-v0.1 encoder model. it is an updated version of `nasa-smd-ibm-st` with better performance (shown below). It's trained with 271 million examples along with a domain-specific dataset of 2.6 million examples from documents curated by NASA Science Mission Directorate (SMD). With this model, we aim to enhance natural language technologies like information retrieval and intelligent search as it applies to SMD NLP applications.
+`nasa-smd-ibm-st-v2` (Indus-ST) is a Bi-encoder sentence transformer model, that is fine-tuned from nasa-smd-ibm-v0.1 encoder model. it is an updated version of `nasa-smd-ibm-st` with better performance (shown below). It's trained with 271 million examples along with a domain-specific dataset of 2.6 million examples from documents curated by NASA Science Mission Directorate (SMD). With this model, we aim to enhance natural language technologies like information retrieval and intelligent search as it applies to SMD NLP applications.
 
 you can also use distilled version of the model here: https://huggingface.co/nasa-impact/nasa-ibm-st.38m
 
@@ -77,6 +77,12 @@ query_embeddings = model.encode(input_queries)
 passage_embeddings = model.encode(input_passages)
 print(util.cos_sim(query_embeddings, passage_embeddings))
 ```
+# Note
+
+This Sentence Transformer Model is released in support of the training and evaluation of the encoder language model ["Indus"](https://huggingface.co/nasa-impact/nasa-smd-ibm-v0.1).
+
+Accompanying paper can be found here: https://arxiv.org/abs/2405.10725
+
 
 ## Citation
 If you find this work useful, please cite using the following bibtex citation: