Bulding my own Diffusion Language Model from scratch was easier than I thought [P]

Since I felt like I was relying on Claude Code a lot recently, I wanted to see how hard it is to implement a diffusion language model from scratch without the help of AI-Generated code. So I built one while waiting for the training for my master’s thesis.

This is what I got after a few hours of training on my MacBook Air M2. I trained on the tiny Shakespeare dataset from Karpathy and prompted “to be, “

To be, fo hend! First her sense ountier to Jupits, be horse. 

Words of wisdom! The model has around 7.5M Params and vocabulary size is 66 (65 chars + [MASK]. I definitely did not train long enough, but I ran out of time for this one.

Projects like these help me make sense of big scary words like (discrete) diffusion, encoder, decoder, tokenizer. Maybe this encourages someone 🙂

Check out the code here if you’re interested: https://github.com/Encrux/simple_dlm

Thanks for reading! Be horse.