Free neural network architectures Image
Sohaib D.
|
free User
Image Generated: 21st March 2025
PROMPT
A comparative schematic diagram of Transformer, RNN, and LSTM architectures. The image should be divided into three sections: RNN - Shows a simple recurrent neural network with sequential processing, highlighting how information flows from one time step to the next. Include an arrow indicating how gradients can vanish over long sequences. LSTM - Displays the cell state, forget gate, input gate, and output gate, showing how LSTM handles long-term dependencies better than RNNs. Transformer - Shows the encoder-decoder structure, multi-head self-attention, and parallel processing, emphasizing the difference from sequential models. The image should use clean colors and clear labels to highlight differences, such as how RNNs process data sequentially while Transformers use self-attention for parallel processing. Include arrows indicating gradient flow issues in RNNs, improvements in LSTMs, and the efficiency of Transformers.Tags
neural network architecturestransformer vs rnnlstm features
Category
Model Version
FLUX 1.1 ProLicense
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