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 **SmolLM2-135M-Humanized** is a fine-tuned version of the [SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) model, optimized using the Direct Preference Optimization (DPO) method. To do this we used the "[Human-Like-DPO-Dataset](https://huggingface.co/datasets/HumanLLMs/Human-Like-DPO-Dataset)" from [Human-Like LLMs](https://huggingface.co/HumanLLMs).
 
-Unlike traditional fine-tuning approaches that aim to improve specific benchmarks or metrics, DPO fine-tuning focuses on aligning the model's behavior with human preferences. This process enhances the model's ability to generate more natural, human-like responses, making it particularly well-suited for conversational applications.
+Unlike traditional fine-tuning datasets that aim to improve specific benchmarks or metrics, the Human-Like-DPO-Dataset focuses on aligning the model's behavior with human preferences. This process enhances the model's ability to generate more natural, human-like responses, making it particularly well-suited for conversational applications.
 
 By emphasizing response quality and relatability, SmolLM2-135M-Humanized is designed to deliver an engaging and intuitive user experience in dialogue-based scenarios.