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@@ -68,9 +68,8 @@ We extended the vocabulary of the base llama model from 32,000 tokens to 57,000
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  <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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  ### Direct Use
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-
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  <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- This model is intended for commercial and research use.
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  ### Out-of-Scope Use
@@ -94,7 +93,7 @@ Like all LLMs, SambaLingo has certain limitations:
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  - Toxicity: The model could inadvertently generate responses containing inappropriate or harmful content.
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  ## Acknowledgments
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- We extend our heartfelt gratitude to the open-source AI community; this endeavor would not have been achievable without open source. SambaNova embraces the open-source community and aspires to actively contribute to this initiative.
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  We would like to give a special thanks to the following groups:
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  - Meta for open sourcing LLama 2 and open sourcing FLORES-200 dataset
@@ -107,7 +106,7 @@ We would like to give a special thanks to the following groups:
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  ## Cite SambaLingo
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  ```
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  @software{sambalingo,
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- title = {{SambaLingo: Language Experts Adapted From Llama}},
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  author = {SambaNova Systems},
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  url = {https://huggingface.co/sambanovasystems/SambaLingo-Japanese-Base}
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  month = {2},
 
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  <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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  ### Direct Use
 
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  <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+ Use of this model is governed by the Meta’s [Llama 2 Community License Agreement](https://ai.meta.com/llama/license/). Please review and accept the license before downloading the model weights.
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  ### Out-of-Scope Use
 
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  - Toxicity: The model could inadvertently generate responses containing inappropriate or harmful content.
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  ## Acknowledgments
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+ We extend our heartfelt gratitude to the open-source AI community; this endeavor would not have been possible without open source. SambaNova embraces the open-source community and aspires to actively contribute to this initiative.
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  We would like to give a special thanks to the following groups:
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  - Meta for open sourcing LLama 2 and open sourcing FLORES-200 dataset
 
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  ## Cite SambaLingo
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  ```
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  @software{sambalingo,
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+ title = {{SambaLingo: Open Source Language Experts}},
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  author = {SambaNova Systems},
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  url = {https://huggingface.co/sambanovasystems/SambaLingo-Japanese-Base}
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  month = {2},