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  2. Attention (machine learning) - Wikipedia

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

    For decoder self-attention, all-to-all attention is inappropriate, because during the autoregressive decoding process, the decoder cannot attend to future outputs that has yet to be decoded. This can be solved by forcing the attention weights w i j = 0 {\displaystyle w_{ij}=0} for all i < j {\displaystyle i<j} , called "causal masking".

  3. File:Decoder self-attention with causal masking, detailed ...

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

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  4. Transformer (deep learning architecture) - Wikipedia

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

    Each decoder layer contains two attention sublayers: (1) cross-attention for incorporating the output of encoder (contextualized input token representations), and (2) self-attention for "mixing" information among the input tokens to the decoder (i.e. the tokens generated so far during inference time).

  5. File:Self-attention in CNN, RNN, and self-attention.svg

    en.wikipedia.org/wiki/File:Self-attention_in_CNN...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  6. DeepSeek - Wikipedia

    en.wikipedia.org/wiki/DeepSeek

    Synthesize 200K non-reasoning data (writing, factual QA, self-cognition, translation) using DeepSeek-V3. SFT DeepSeek-V3-Base on the 800K synthetic data for 2 epochs. Apply the same GRPO RL process as R1-Zero with rule-based reward (for reasoning tasks), but also model-based reward (for non-reasoning tasks, helpfulness, and harmlessness).

  7. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Image and video generators like DALL-E (2021), Stable Diffusion 3 (2024), [44] and Sora (2024), use Transformers to analyse input data (like text prompts) by breaking it down into "tokens" and then calculating the relevance between each token using self-attention, which helps the model understand the context and relationships within the data.

  8. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  9. React Native - Wikipedia

    en.wikipedia.org/wiki/React_Native

    React Native is an open-source UI software framework developed by Meta Platforms (formerly Facebook Inc.). [3] It is used to develop applications for Android , [ 4 ] : §Chapter 1 [ 5 ] [ 6 ] Android TV , [ 7 ] iOS , [ 4 ] : §Chapter 1 [ 6 ] macOS , [ 8 ] tvOS , [ 9 ] Web , [ 10 ] Windows [ 8 ] and UWP [ 11 ] by enabling developers to use the ...