Large context window is a desirable feature in large language models (LLMs). However, due to high fine-tuning costs, scarcity of long texts, and catastrophic values introduced by new token positions, current ex
Attention-based context window extensions: Han et al. (2023), Xiao et al. (2023), 和 Ratner et al. (2022) 提出了通过操纵注意力机制来扩展输入上下文的方法。 Fine-tuning based approaches: 一些研究专注于如何有效地微调预训练的LLMs,以适应修改后的位置嵌入,例如通过在目标长度上进行大量微调。 这些...
Main idea 这篇论文是为了解决长文本问题,提出位置插值(Position Interpolation, PI)方法,用于扩展使用旋转位置编码(Rotary Position Embedding, RoPE)(引用)的大型语言模型(LLMs)的上下文窗口大小。基…
In the realm of large language models (LLMs), extending the context window for long text processing is crucial for enhancing performance. This paper introduces SBA-RoPE (Segmented Base Adjustment for Rotary Position Embeddings), a novel approach designed to efficiently extend the context wi...
This is the official repo for "Extending LLMs' Context Window with 100 Samples".Preprint Introduction We introduce 'Entropy-Aware ABF' that supports efficient context window extension of RoPE-based LLMs with only 100 samples. The repository contains code and data to reproduce our model. ...
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no_grad(): # Predict hidden states features for each layer hidden_states_1, mems_1 = model(tokens_tensor_1) # We can re-use the memory cells in a subsequent call to attend a longer context hidden_states_2, mems_2 = model(tokens_tensor_2, mems=mems_1)And how to use TransfoXLLM...
I think Claude2 has a context window of 100k tokens which was recently released but as you said we may see newer LLMs which could potentially even exceed this. Thanks for sharing @warcoder. Jonathan Bown Posted 2 years ago arrow_drop_up1more_vert This is really cool! Great post @war...