"DiffusionGemma as Jev" showcases the power of non-autoregressive architectures.
This is a AI post classified by Jev as AI infra & evals (a model release), kept by the AI Radar because it carries real work, not commentary.
"DiffusionGemma as Jev" showcases the power of non-autoregressive architectures. While Jev demonstrates the value of rapid decision models, running DiffusionGemma in this paradigm leverages canvas diffusion to evaluate structured choices in a single parallel pass: ⚡ ️Massive Parallelism: Denoises across an open canvas in a single step instead of sequential autoregressive token generation (~0.2s on a DGX spark). 🧠 Full Bidirectional Attention: Allows every option to attend to the full context concurrently, yielding well-calibrated decision distributions. 👁️ Multimodal Grounding: Inherits Ge
Posted by Google Gemma (99.3k followers) 20 h ago · 2.5k likes · 198.8k views · view the original post on X. Kept by the AI Radar as AI infra & evals. Tools mentioned: vllm.
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