论文:《DeepSeek LLM Scaling Open-Source Language Models with Longtermism》 链接:arxiv.org/pdf/2401.0295 DeepSeek-v1的架构参考LLaMA-2,主要区别是预训练数据规模更大,在层数上,7B版本采用30层网络,67B版本采用95层网络。FFN使用SwiGLU激活函数。 DeepSeek-v1
模型结构 标准化:为了提高训练的稳定性,标准化每个transformer子层输入来替换原始标准化输出;(Open pre-trained transformer language models)使用PaLM中的SwiGLu作为激活函数,使用SwiGLU来代替Relu,dinmension由PaLM的4d->2/3*4d 旋转EMbedding:采用旋转Embedding来代替绝对位置Embedding ...
--need_layers: We support [all,last,mid], which specify all the layers, the last layer, the mid layer (16 for 32-layer models) for getting hidden state information. Multi-Choice Generation python run_mmlu.py \ --source YOUR_DATA_PATH \ --type qa \ --ra none \ --outfile YOUR_OUT...
We also benchmarked the results of these models against closed-source models such as Gemini and GPT-4 on inference with context, showcasing the potential of narrowing the gap between open-source and closed-source models when context is provided. Our work demonstrates the capabilities of LLMs in...
Code for inference in decoder-only LLMs. The code is based on transformers. - Inference-in-Decoder-Only-Models/collect.py at master · ShiyuNee/Inference-in-Decoder-Only-Models
在当今的人工智能和自然语言处理(NLP)领域,大语言模型(Large Language Models, LLMs)如GPT系列已成为研究热点,并展现出强大的语言理解和生成能力。这些模型的一个显著特点是它们大多采用Decoder-only架构,而非传统的Encoder-Decoder或Encoder-Only架构。那么,为何Decoder-only架构会在大语言模型中占据主导地位呢?本文将深...
近年来,大型语言模型(Large Language Models,LLM)在自然语言处理领域取得了显著的进展。这些模型基于深度学习技术,通过对大量文本数据进行训练,能够理解和生成人类语言。然而,细心观察可以发现,现在的大语言模型基本上都是Decoder-only的架构。那么,为什么会出现这种情况呢?本文将重点探讨这个话题,并介绍Decoder-only架构的...
Decoder-only models, such as GPT, have demonstrated superior performance in many areas compared to traditional encoder-decoder structure transformer models. Over the years, end-to-end models based on the traditional transformer structure, like MOTR, have achieved remarkable performance in multi-object ...
This motivates the question: “Can large pretrained models trained on massive amounts of time-series data learn temporal patterns that can be useful for time-series forecasting on previously unseen datasets?” In particular, can we design a time-series foundation model that obtains good zero-shot...
multilayered architectures that leverage vast datasets and often incorporate thousands of predictive models. The maintenance and enhancement of these models is a labor intensive process that requires extensive feature engineering. This approach not only exacerbates technical debt but also hampers innovation ...