DeepSeek-R1 is a reasoning model trained via large-scale reinforcement learning (RL) without the need for supervised fine-tuning (SFT). It demonstrates remarkable performance in reasoning tasks, including self-verification and reflection. The model addresses challenges such as endless repetition and poor readability, and achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
DeepSeek-R1 is an advanced reasoning model that leverages large-scale reinforcement learning to achieve significant performance in reasoning tasks. It incorporates cold-start data before RL to enhance reasoning capabilities and address issues like repetition and readability. DeepSeek-R1 is designed to provide high accuracy in reasoning tasks and is suitable for a wide range of applications.
This repository provides code and data for automatic depression detection using a GRU/BiLSTM-based model. It includes an emotional audio-textual corpus designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder.
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