{"slug": "diffusiongemma-grammar-and-word-merging-issues-in-question-generation", "title": "DiffusionGemma Grammar and Word-Merging Issues in Question Generation", "summary": "A user running RedHatAI/diffusiongemma-26B-A4B-it-FP8-dynamic via vLLM in Docker reports word-merging and grammar issues in a marine-domain question-generation application, such as 'upcomingbunkering operation' instead of 'upcoming bunkering operation', while the same model and server perform well in a RAG chatbot. The user seeks to determine whether the problem stems from the diffusion model's limitations or from configuration differences like canvas_length=256 and diffusion_entropy_bound=0.1.", "body_md": "Hi everyone,\n\nI am currently running **RedHatAI/diffusiongemma-26B-A4B-it-FP8-dynamic** using vLLM through Docker.\n\nMy current vLLM command is:\n\n```\nvllm serve --model RedHatAI/diffusiongemma-26B-A4B-it-FP8-dynamic \\\n  --trust-remote-code \\\n  --attention-backend TRITON_ATTN \\\n  --max-num-seqs 4 \\\n  --max-model-len 8192 \\\n  --gpu-memory-utilization 0.78 \\\n  --generation-config vllm \\\n  --hf-overrides '{\"diffusion_sampler\":\"entropy_bound\",\"diffusion_entropy_bound\":0.1}' \\\n  --diffusion-config '{\"canvas_length\":256}' \\\n  --host 0.0.0.0 \\\n  --port 8085\n```\n\nI am using the same model/server in two different applications:\n\nInterestingly, the model works reasonably well in the RAG chatbot. I don’t see noticeable grammar problems or word-merging issues there.\n\nHowever, in the **marine-domain question-generation application**, I sometimes get outputs with:\n\nFor example, I can get output similar to:\n\n`upcomingbunkering operation`\n\ninstead of:\n\n`upcoming bunkering operation`\n\nI also see cases where the generated question structure or grammar is not correct.\n\nThe important part is that **the same model and vLLM server are being used**, but the problem is much more noticeable in the question-generation workflow.\n\nI understand that DiffusionGemma is experimental and that its output quality may not be comparable to standard autoregressive Gemma models. However, I am trying to understand whether the behavior I’m seeing is actually a model limitation or whether there is something different in my question-generation pipeline that I am missing.\n\nCould the difference be caused by things such as:\n\n`canvas_length=256`\n\n`entropy_bound`\n\n/ `diffusion_entropy_bound`\n\nHas anyone experienced similar **word-merging or grammar issues with DiffusionGemma specifically during question generation or structured output generation**?\n\nAny suggestions on what I should compare or test between the RAG and question-generation pipelines would be appreciated. I would particularly like to know whether this is expected behavior from the diffusion generation approach or whether there is a configuration issue I should investigate.", "url": "https://wpnews.pro/news/diffusiongemma-grammar-and-word-merging-issues-in-question-generation", "canonical_source": "https://discuss.huggingface.co/t/diffusiongemma-grammar-and-word-merging-issues-in-question-generation/178788#post_1", "published_at": "2026-08-18 08:49:57+00:00", "updated_at": "2026-08-18 09:12:04.249814+00:00", "lang": "en", "topics": ["large-language-models", "generative-ai"], "entities": ["RedHatAI/diffusiongemma-26B-A4B-it-FP8-dynamic", "vLLM", "Docker"], "alternates": {"html": "https://wpnews.pro/news/diffusiongemma-grammar-and-word-merging-issues-in-question-generation", "markdown": "https://wpnews.pro/news/diffusiongemma-grammar-and-word-merging-issues-in-question-generation.md", "text": "https://wpnews.pro/news/diffusiongemma-grammar-and-word-merging-issues-in-question-generation.txt", "jsonld": "https://wpnews.pro/news/diffusiongemma-grammar-and-word-merging-issues-in-question-generation.jsonld"}}