content.raw: 🎌 Two months in, 
content.type: text
content.value: 🎌 Two months in, 
content.href: https://github.com/takara-ai/go-attention
content.raw: https://github.com/takara-ai/go-attention
content.type: link
content.raw:  has passed 429 stars on GitHub.
content.type: text
content.value:  has passed 429 stars on GitHub.
content.type: new_line
content.type: new_line
content.raw: We built this library at takara.ai to bring attention mechanisms and transformer layers to Go — in a form that's lightweight, clean, and dependency-free.
content.type: text
content.value: We built this library at takara.ai to bring attention mechanisms and transformer layers to Go — in a form that's lightweight, clean, and dependency-free.
content.type: new_line
content.type: new_line
content.raw: We’re proud to say that every part of this project reflects what we set out to do.
content.type: text
content.value: We’re proud to say that every part of this project reflects what we set out to do.
content.type: new_line
content.type: new_line
content.raw: - Pure Go — no external dependencies, built entirely on the Go standard library
content.type: text
content.value: - Pure Go — no external dependencies, built entirely on the Go standard library
content.type: new_line
content.raw: - Core support for DotProductAttention and MultiHeadAttention
content.type: text
content.value: - Core support for DotProductAttention and MultiHeadAttention
content.type: new_line
content.raw: - Full transformer layers with LayerNorm, feed-forward networks, and residual connections
content.type: text
content.value: - Full transformer layers with LayerNorm, feed-forward networks, and residual connections
content.type: new_line
content.raw: - Designed for edge, embedded, and real-time environments where simplicity and performance matter
content.type: text
content.value: - Designed for edge, embedded, and real-time environments where simplicity and performance matter
content.type: new_line
content.type: new_line
content.raw: Thank you to everyone who has supported this so far — the stars, forks, and feedback mean a lot.
content.type: text
content.value: Thank you to everyone who has supported this so far — the stars, forks, and feedback mean a lot.
rawContent: 🎌 Two months in, https://github.com/takara-ai/go-attention has passed 429 stars on GitHub.
  
  We built this library at takara.ai to bring attention mechanisms and transformer layers to Go — in a form that's lightweight, clean, and dependency-free.
  
  We’re proud to say that every part of this project reflects what we set out to do.
  
  - Pure Go — no external dependencies, built entirely on the Go standard library
  - Core support for DotProductAttention and MultiHeadAttention
  - Full transformer layers with LayerNorm, feed-forward networks, and residual connections
  - Designed for edge, embedded, and real-time environments where simplicity and performance matter
  
  Thank you to everyone who has supported this so far — the stars, forks, and feedback mean a lot.
reactions.reaction: 👍
reactions.users: John6666
commentators._id: 6694524f8988b2388e3bc94c
commentators.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/6694524f8988b2388e3bc94c/Cef5cGlPeF3S18mY79A3z.jpeg
commentators.fullname: Thomas Nguyen
commentators.name: ThomasTheMaker
commentators.type: user
commentators._id: 6613f7ae43c4456e13ecbdcc
commentators.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/aqVOJmgtsBbB6BFeLpL7h.jpeg
commentators.fullname: Jordan Legg
commentators.name: takarajordan
commentators.type: user