Post
3,557
I made a 1.1M ModernBERT encoder play Doom in real time on a CPU
Some time ago, VAGO Solutions released SauerkrautLM-Doom-MultiVec-1.3M, a tiny model trained to play Doom Defend the Center scenario from 31k human gameplay examples.
My first thought: cool! I love both Doom and Small Language Models.
Then another idea: I bet I can do better :-)
What I did?
- evaluated the original model and found it's better than reported
- changed a bit the architecture
- generated SFT data with a scripted oracle
- SFT + PPO refinement on consumer hardware
Got a smaller, faster and killer model
Can even fit a floppy with int8 quantization 💾
Watch it play/read the article: anakin87/tiny-doom-defender
Some time ago, VAGO Solutions released SauerkrautLM-Doom-MultiVec-1.3M, a tiny model trained to play Doom Defend the Center scenario from 31k human gameplay examples.
My first thought: cool! I love both Doom and Small Language Models.
Then another idea: I bet I can do better :-)
What I did?
- evaluated the original model and found it's better than reported
- changed a bit the architecture
- generated SFT data with a scripted oracle
- SFT + PPO refinement on consumer hardware
Got a smaller, faster and killer model
Can even fit a floppy with int8 quantization 💾
Watch it play/read the article: anakin87/tiny-doom-defender
