Update README.md

README.md

@@ -10,9 +10,9 @@ tags:
 pipeline_tag: sentence-similarity
 ---
 
-# Model Card for nasa-smd-ibm-v0.1
+# Model Card for nasa-smd-ibm-st-v2
 
-`nasa-smd-ibm-st-v2` is improved version of Bi-encoder sentence transformer model (`nasa-smd-ibm-st`), that is fine-tuned from nasa-smd-ibm-v0.1 encoder model. 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` is a Bi-encoder sentence transformer model, that is fine-tuned from nasa-smd-ibm-v0.1 encoder model. 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.
 
 ## Model Details
 - **Base Model**: nasa-smd-ibm-v0.1
@@ -41,19 +41,19 @@ Following models are evaluated:
 3. RoBERTa-base [roberta-base]
 4. nasa-smd-ibm-rtvr_v0.1 [nasa-impact/nasa-smd-ibm-st]
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/QvuEkZJjDGNllRyzl3Oh6.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/eGRC1_EGCp5yAIQiM8Gav.png)
 
 Figure: BEIR Evaluation Metrics
 
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/J3iuPWaGp_qTbllPFpchi.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/2dTtMDcbEP9I3QkmxGbO4.png)
 
 Figure: Retrieval Benchmark Evaluation
 
 ## Uses
-- Information Retrieval
+- Information Retreival
 - Sentence Similarity Search
-- Retrieval Augmented Generation
 
 For NASA SMD related, scientific usecases.
 
@@ -62,7 +62,7 @@ For NASA SMD related, scientific usecases.
 ```python
 
 from sentence_transformers import SentenceTransformer, util
-model = SentenceTransformer('path_to_model')
+model = SentenceTransformer('path_to_slate_model')
 input_queries = [
 'query: how much protein should a female eat', 'query: summit define']
 input_passages = [