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Jordan Legg PRO

takarajordan
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https://takara.ai

AI & ML interests

Chief AI Officer @takara.ai. Diffusion, Inference optimisation and all things MultiModal.

Recent Activity

replied to their post 2 days ago
🎌 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.
replied to their post 3 days ago
🎌 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.
posted an update 3 days ago
🎌 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.
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🎌 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.
View all Posts

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