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@@ -23,7 +23,7 @@ pipeline_tag: sentence-similarity
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  ## Training Data
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/ZjcHW24iKsvUYBhoL7eMM.png)
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- Figure:Open dataset sources for sentence transformers (271M in total)
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  Additionally, 2.6M abstract + title pairs collected from NASA SMD documents.
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@@ -43,6 +43,9 @@ Following models are evaluated:
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  5. nasa-smd-ibm-rtvr_v0.1
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/zbeBb8mh0wgdTu1Gc-j1I.png)
 
 
 
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  ## Uses
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  - Information Retreival
@@ -50,6 +53,21 @@ Following models are evaluated:
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  For NASA SMD related, scientific usecases.
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  ## Citation
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  If you find this work useful, please cite using the following bibtex citation:
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  ## Training Data
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/ZjcHW24iKsvUYBhoL7eMM.png)
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+ Figure: Open dataset sources for sentence transformers (271M in total)
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  Additionally, 2.6M abstract + title pairs collected from NASA SMD documents.
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  5. nasa-smd-ibm-rtvr_v0.1
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61099e5d86580d4580767226/zbeBb8mh0wgdTu1Gc-j1I.png)
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+ Figure: BEIR Evaluation Metrics
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+
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+
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  ## Uses
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  - Information Retreival
 
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  For NASA SMD related, scientific usecases.
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+ ### Usage
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+
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+ ```python
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+
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+ from sentence_transformers import SentenceTransformer, util
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+ model = SentenceTransformer('path_to_slate_model')
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+ input_queries = [
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+ 'query: how much protein should a female eat', 'query: summit define']
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+ input_passages = [
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+ "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day.
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+ But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
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+ "Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments."]
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+ query_embeddings = model.encode(input_queries) passage_embeddings = model.encode(input_passages) print(util.cos_sim(query_embeddings, passage_embeddings))
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+ ```
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+
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  ## Citation
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  If you find this work useful, please cite using the following bibtex citation:
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