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Transformer Explainer Really cool interactive tool to learn about the inner workings of a Transformer model. Apparently, it runs a GPT-2 instance locally in the user's browser and allows you to experiment with your own inputs. This is a nice tool to learn more about the different components inside... show more

elvis

307,148 subscribers

121,895 次观看 • 1 年前 •via X (Twitter)

教育科学技术

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10 条评论

elvis 的头像

elvis1 年前

Here is a short video going over the tool:

Eli Luong, MD, DABA 的头像

Eli Luong, MD, DABA1 年前

beautiful tool 🥰

Manny 的头像

Manny1 年前

This is great thanks for sharing.

GPT.Biz 的头像

GPT.Biz1 年前

This looks like an amazing tool to deepen your understanding of AI models in a hands-on way!

Duen Horng "Polo" Chau 的头像

Duen Horng "Polo" Chau1 年前

Thanks for sharing our work! Congrats @cho_aeree @gracekimcy @alexkarpekov @alec_helbling @SeongminLeee @Jay4w @Ben_Hoov , all students at @gtcomputing !

Tim Hulse 的头像

Tim Hulse1 年前

Thank you for not using “The cat sat on the ___”

Subba Reddy 的头像

Subba Reddy1 年前

Transformer explainer : should be mandatory read for all ML undergrad courses. Bar raiser in interactive inner workings of a tool. we need similar interactive visual tools for "code repos" to grok THE FLOW from UI -> Auth ->server ->various layers ->DB

Nathanael 的头像

Nathanael1 年前

the easiest way to understand transformers. Great work!

micke 的头像

micke1 年前

thanks elvis

RUH-ROH 的头像

RUH-ROH1 年前

Thanks for the share!

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Transformer Explainer Interactive Learning of Text-Generative Models discuss: Transformers have revolutionized machine learning, yet their inner workings remain opaque to many. We present Transformer Explainer, an interactive visualization tool designed for non-experts to learn about Transformers through the GPT-2 model. Our tool helps users understand complex Transformer concepts by integrating a model overview and enabling smooth transitions across abstraction levels of mathematical operations and model structures. It runs a live GPT-2 instance locally in the user's browser, empowering users to experiment with their own input and observe in real-time how the internal components and parameters of the Transformer work together to predict the next tokens. Our tool requires no installation or special hardware, broadening the public's education access to modern generative AI techniques.

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