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@@ -42,10 +42,6 @@ The model may also serve educational purposes in highlighting the importance of
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  ### Out-of-Scope
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  Use of this model to generate content for public consumption or in any application outside of controlled, ethical research settings is strongly discouraged and considered out-of-scope.
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- ### Usage
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-
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- Below we share some code snippets on how to get quickly started with running the model. First make sure to `pip install -U transformers`, then copy the snippet from the section that is relevant for your usecase.
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  ## Training Data
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  The "Gemma-2b-it" model was fine-tuned on a dataset comprised of uncensored and toxic content, sourced from various online forums and platforms known for less moderated interactions. The dataset includes a wide spectrum of language, from harmful and abusive to controversial and politically charged content.
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  Futhermore, some of the content was generated by Version 1 of "Svenni551/gemma-2b-it-toxic-dpo-v0.2".
@@ -71,6 +67,10 @@ Users of this model are advised to:
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  - Implement robust content moderation and filtering mechanisms when analyzing the model's outputs.
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  - Engage with ethical review boards or oversight committees when planning research involving this model.
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  #### Running the model on a CPU
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  ### Out-of-Scope
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  Use of this model to generate content for public consumption or in any application outside of controlled, ethical research settings is strongly discouraged and considered out-of-scope.
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  ## Training Data
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  The "Gemma-2b-it" model was fine-tuned on a dataset comprised of uncensored and toxic content, sourced from various online forums and platforms known for less moderated interactions. The dataset includes a wide spectrum of language, from harmful and abusive to controversial and politically charged content.
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  Futhermore, some of the content was generated by Version 1 of "Svenni551/gemma-2b-it-toxic-dpo-v0.2".
 
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  - Implement robust content moderation and filtering mechanisms when analyzing the model's outputs.
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  - Engage with ethical review boards or oversight committees when planning research involving this model.
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+ ### Usage
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+
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+ Below we share some code snippets on how to get quickly started with running the model. First make sure to `pip install -U transformers`, then copy the snippet from the section that is relevant for your usecase.
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+
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  #### Running the model on a CPU
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