srijithrajamohan commited on
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5720d30
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1 Parent(s): f0ab18f

Typo fix (#6)

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- Removed leftover references to the Quora data (e559634d9055f477347301d8357447002b370dd2)

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  1. README.md +3 -3
README.md CHANGED
@@ -41,7 +41,7 @@ model-index:
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  # SentenceTransformer based on Alibaba-NLP/gte-modernbert-base
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- This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Alibaba-NLP/gte-modernbert-base](https://huggingface.co/Alibaba-NLP/gte-modernbert-base) on the Quora csv dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity for the purpose of semantic caching.
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  ## Model Details
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@@ -84,7 +84,7 @@ Then you can load this model and run inference.
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  from sentence_transformers import SentenceTransformer
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  # Download from the 🤗 Hub
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- model = SentenceTransformer("redis/langcache-embed-v1")
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  # Run inference
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  sentences = [
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  'Will the value of Indian rupee increase after the ban of 500 and 1000 rupee notes?',
@@ -126,7 +126,7 @@ print(similarities.shape)
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  #### Medical
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  * Dataset: Medical dataset
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- * Size:
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  * Columns: <code>question_1</code>, <code>question_2</code>, and <code>label</code>
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  ## Citation
 
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  # SentenceTransformer based on Alibaba-NLP/gte-modernbert-base
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+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Alibaba-NLP/gte-modernbert-base](https://huggingface.co/Alibaba-NLP/gte-modernbert-base) on the Medical dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity for the purpose of semantic caching in the medical domain.
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  ## Model Details
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  from sentence_transformers import SentenceTransformer
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  # Download from the 🤗 Hub
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+ model = SentenceTransformer("redis/langcache-embed-medical-v1")
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  # Run inference
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  sentences = [
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  'Will the value of Indian rupee increase after the ban of 500 and 1000 rupee notes?',
 
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  #### Medical
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  * Dataset: Medical dataset
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+ * Size:
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  * Columns: <code>question_1</code>, <code>question_2</code>, and <code>label</code>
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  ## Citation