rti/gptvis
Understanding Transformers Using A Minimal Example
This project helps machine learning engineers and researchers understand how Transformer Large Language Models work internally. It takes a simplified Transformer model and a small dataset as input, then visualizes the model's internal states, showing how information flows and how the attention mechanism operates. This allows a detailed, step-by-step observation of the core processes, making complex concepts tangible.
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Use this if you are a machine learning engineer or researcher struggling to form a mental model of Transformer LLMs due to the vast number of internal parameters.
Not ideal if you are looking for a tool to develop or deploy large-scale LLMs, as this focuses purely on explaining simplified model mechanics.
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52
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Language
Python
License
MIT
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Last pushed
May 05, 2025
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