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  This model is a **two-fold fine-tuned** [Flan-T5 model](https://huggingface.co/google/flan-t5-base) firstly on the [SAMSUM](https://huggingface.co/datasets/samsum) dataset followed by further fine-tuning using **Reinforcement Learning from AI Feedback(RLAIF)** to detoxify model outputs. <br>
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  Anthropic's Costitutional AI [paper](https://arxiv.org/abs/2212.08073) from 2022, provides some amazing insights on how RLAIF can be leveraged. Do check out if interested!<br>
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- More, specifically I've fine-tuned this model on a single downstream task of Dialogue Summarization on the above mentioned dataset with a primary objective of reduced toxicity in generated summaries.
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  ## Model description
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  This Model has the same architecture and Parameters as its base model. Please refer to this [link](https://arxiv.org/abs/2210.11416) to know more about the model details.
 
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  This model is a **two-fold fine-tuned** [Flan-T5 model](https://huggingface.co/google/flan-t5-base) firstly on the [SAMSUM](https://huggingface.co/datasets/samsum) dataset followed by further fine-tuning using **Reinforcement Learning from AI Feedback(RLAIF)** to detoxify model outputs. <br>
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  Anthropic's Costitutional AI [paper](https://arxiv.org/abs/2212.08073) from 2022, provides some amazing insights on how RLAIF can be leveraged. Do check out if interested!<br>
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+ More specifically, I've fine-tuned this model on a single downstream task of Dialogue Summarization on the above mentioned dataset with a primary objective of reduced toxicity in generated summaries.
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  ## Model description
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  This Model has the same architecture and Parameters as its base model. Please refer to this [link](https://arxiv.org/abs/2210.11416) to know more about the model details.