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  2. File:Multiheaded attention, block diagram.png - Wikipedia

    en.wikipedia.org/wiki/File:Multiheaded_attention...

    Multiheaded_attention,_block_diagram.png (656 × 600 pixels, file size: 32 KB, MIME type: image/png) This is a file from the Wikimedia Commons . Information from its description page there is shown below.

  3. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Multiheaded attention, block diagram Exact dimension counts within a multiheaded attention module. One set of (,,) matrices is called an attention head, and each layer in a transformer model has multiple attention heads. While each attention head attends to the tokens that are relevant to each token, multiple attention heads allow the model to ...

  4. Attention (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Attention_(machine_learning)

    During the deep learning era, attention mechanism was developed to solve similar problems in encoding-decoding. [1]In machine translation, the seq2seq model, as it was proposed in 2014, [24] would encode an input text into a fixed-length vector, which would then be decoded into an output text.

  5. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Each attention head learns different linear projections of the Q, K, and V matrices. This allows the model to capture different aspects of the relationships between words in the sequence simultaneously, rather than focusing on a single aspect. By doing this, multi-head attention ensures that the input embeddings are updated from a more varied ...

  6. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    When each head calculates, according to its own criteria, how much other tokens are relevant for the "it_" token, note that the second attention head, represented by the second column, is focusing most on the first two rows, i.e. the tokens "The" and "animal", while the third column is focusing most on the bottom two rows, i.e. on "tired ...

  7. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    Graph attention network is a combination of a GNN and an attention layer. The implementation of attention layer in graphical neural networks helps provide attention or focus to the important information from the data instead of focusing on the whole data. A multi-head GAT layer can be expressed as follows:

  8. Class diagram - Wikipedia

    en.wikipedia.org/wiki/Class_diagram

    In software engineering, a class diagram [1] in the Unified Modeling Language (UML) is a type of static structure diagram that describes the structure of a system by showing the system's classes, their attributes, operations (or methods), and the relationships among objects. The class diagram is the main building block of object-oriented modeling.

  9. Functional block diagram - Wikipedia

    en.wikipedia.org/wiki/Functional_block_diagram

    The block diagram can use additional schematic symbols to show particular properties. Since the late 1950s, functional block diagrams have been used in a wide range applications, from systems engineering to software engineering. They became a necessity in complex systems design to "understand thoroughly from exterior design the operation of the ...