The paper focuses on aligning language models with human preferences for real-world applications. It discusses the drawbacks of reinforcement learning (RL) and direct preference optimization (DPO) in achieving this goal….
Continue readingTinyLlama, a compact 1.1B language model pretrained on around 1 trillion tokens for roughly 3 epochs, shows remarkable performance in various downstream tasks. Despite its small size, it outperforms other…
Continue readingThis research paper discusses the Backpack, an alternative to the Transformer model, and its application in Chinese language modeling. The Backpack improves interpretability in English language modeling by breaking down…
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