Tom Aarsen commited on
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Undo weird unicode changes

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  1. README.md +5 -5
README.md CHANGED
@@ -18,7 +18,7 @@ Check out our [paper](https://arxiv.org/abs/2411.12644) for more details!
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  We also offer 400M-size model [Salesforce/SFR-Embedding-Code-400_R](https://huggingface.co/Salesforce/SFR-Embedding-Code-400M_R)
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  ### Ethical Considerations
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- This release is for research purposes only in support of an academic paper. Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes. We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model. We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting use cases, particularly for high-risk scenarios where errors or misuse could significantly impact peopleÔÇÖs lives, rights, or safety. For further guidance on use cases, refer to our [AUP](https://www.salesforce.com/content/dam/web/en_us/www/documents/legal/Agreements/policies/ExternalFacing_Services_Policy.pdf) and [AI AUP](https://www.salesforce.com/content/dam/web/en_us/www/documents/legal/Agreements/policies/ai-acceptable-use-policy.pdf).
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  ### License Statement:
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  Users need to make their own assessment regarding any obligations or responsibilities under the corresponding licenses or terms and conditions pertaining to the original datasets and data. This release is for research purposes only in support of an academic paper.
@@ -38,14 +38,14 @@ This released model is a fine-tuned version of Gemma and Gemma is provided under
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  | CodeSage-Small | 130M | 54.4 |
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- SFR-Embedding Team (ÔÇá indicates co-leaders)
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  * Ye Liu
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  * Rui Meng
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  * Shafiq Rayhan Joty
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  * Silvio Savarese
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- * Caiming Xiong ÔÇá
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- * Yingbo Zhou ÔÇá
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- * Semih Yavuz ÔÇá
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  ## How to run
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  We also offer 400M-size model [Salesforce/SFR-Embedding-Code-400_R](https://huggingface.co/Salesforce/SFR-Embedding-Code-400M_R)
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  ### Ethical Considerations
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+ This release is for research purposes only in support of an academic paper. Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes. We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model. We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting use cases, particularly for high-risk scenarios where errors or misuse could significantly impact people’s lives, rights, or safety. For further guidance on use cases, refer to our [AUP](https://www.salesforce.com/content/dam/web/en_us/www/documents/legal/Agreements/policies/ExternalFacing_Services_Policy.pdf) and [AI AUP](https://www.salesforce.com/content/dam/web/en_us/www/documents/legal/Agreements/policies/ai-acceptable-use-policy.pdf).
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  ### License Statement:
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  Users need to make their own assessment regarding any obligations or responsibilities under the corresponding licenses or terms and conditions pertaining to the original datasets and data. This release is for research purposes only in support of an academic paper.
 
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  | CodeSage-Small | 130M | 54.4 |
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+ SFR-Embedding Team ( indicates co-leaders)
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  * Ye Liu
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  * Rui Meng
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  * Shafiq Rayhan Joty
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  * Silvio Savarese
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+ * Caiming Xiong
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+ * Yingbo Zhou
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+ * Semih Yavuz
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  ## How to run
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