decoder-only有个值得说的特点是推理可以使用KV-cache技术,原因是casual attention mask可以让历史不可改变,只需要把past的attention矩阵存下来,新来token只需要计算新的一行,列直接填充-inf即可。(当然这个也带了灾难性的低计算访存比,增加了部署加速难度) decoder-only attention mask GPT从3.5开始才真正的大放异彩,...
1. prefix Decoder 系 2. causal Decoder 系 3. Encoder-Decoder 三、训练目标 四、为何现在的大模型大部分是Decoder only结构? 五、为什么有涌现能力 六、大模型的优缺点 本篇从目前开源的主流模型体系架构出发,对大模型做比较基础的介绍。 本篇主要以范围较宽的面试题形式,深入介绍大模型基础,大家可以参考着本...
从名字上可以猜测出来, 它是基于长度的解码器.LengthFieldBasedFrameDecoder是一个基于长度解码器, 它是N...
Figure 2: Encoder-Decoder framework (left) and Regularized Encoder-Decoder framework (right). 3.2 Regularized Encoder-Decoder Though the decoder-only Language Model (LM) is simply a decoder, it is still difficult to be compared with an Encoder-Decoder (ED) structure because this decoder handles...
Encoder-Decoder(编码-解码)是深度学习中非常常见的一个模型框架,比如无监督算法的auto-encoding就是用编码-解码的结构设计并训练的;比如这两年比较热的image caption的应用,就是CNN-RNN的编码-解码框架;再比如神经网络机器翻译NMT模型,往往就是LSTM-LSTM的编码-解码框架。因此,准确的说,Encoder-Decoder并不是一个具体...
D3D12DDIARG_CREATE_VIDEO_DECODER_HEAP_0033結構 D3D12DDIARG_CREATE_VIDEO_DECODER_HEAP_0072 結構 D3D12DDIARG_CREATE_VIDEO_ENCODER_0082_0結構 D3D12DDIARG_CREATE_VIDEO_ENCODER_HEAP_0080_2結構 D3D12DDIARG_CREATE_VIDEO_EXTENSION_COMMAND_0063 結構 D3D1...
啟用DIRECT 空間模式。 請檢查D3D12DDI_VIDEO_ENCODER_CODEC_CONFIGURATION_SUPPORT_H264_FLAG_0080_DIRECT_SPATIAL_ENCODING_SUPPORT旗標以取得支援。 言論 如需一般資訊,請參閱D3D12 視訊編碼。 要求 要求價值 最低支援的用戶端Windows 11 (WDDM 3.0)
tensorflowglmcvaeencoder-decoder-modelgnnscanpycell-cell-interactioncell-cell-communicationsquidpy UpdatedJan 15, 2024 Python A deep generative model to predict aircraft actual trajectories using high dimensional weather data lstmgenerative-modeltrajectory-generationspatio-temporalencoder-decodertrajectory-prediction...
Encoder-Decoder Without Attention In this section, we will develop a baseline in performance on the problem with an encoder-decoder model without attention. We will fix the problem definition at input and output sequences of 5 time steps, the first 2 elements of the input sequence in the outp...
Autoencoders discover latent variables by passing input data through a “bottleneck” before it reaches the decoder. This forces the encoder to learn to extract and pass through only the information most conducive to accurately reconstructing the original input. ...