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Rename 이문세 원곡.mp3 to lee.mp3
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Rename 신비한 바다의 나디아 오프닝 (mp3cut.net).mp3 to nadia.mp3
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Purge remaining "9B" / "Darwin V5" strings from index.html
Three leftover strings were still rendering wrong sizing/version in the UI even after the main rebrand pass: - Sidebar logo name: "Darwin-9B" -> "Darwin-4B" - Footer model hint: "9B Dense . BF16 . 131K ctx" -> "Gemma4 4B . BF16 . 131K ctx" - Vision sample toast: "Vision not supported on 9B model" -> "Vision tower not loaded in this build" (accurate; vision_tower weights come up as UNEXPECTED in the Gemma4ForConditionalGeneration load report, so vision is not actually functional at runtime) - Example card prompt: "Darwin V5 evolutionary merge" -> "Darwin V6" (the model repo ships darwin_v6_report.json, so V6 is the real name)e5e6a84 -
Update README.md
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Rebrand UI to Darwin-4B-David and fix Gradio Radio value mismatch
- Replace all DECKARD-E4B-Opus strings in index.html with Darwin-4B-David (title, header pill, model card, sidebar pill, 2 model card links, welcome badge set, general preset, sysPrompt textarea). - Arch/stats: "Dense 9B" -> "Gemma4 4B", "Qwen3.5 Dense" -> "Gemma4 Multimodal", "9B params" -> "4B params", description line updated to reflect Gemma4 + Vision/Audio + 131K context. - Fix gradio.exceptions.Error: the frontend was sending '⚡ Fast Mode (direct answer)' which is not in the Radio choices list ['⚡ Fast Mode', '🧠 Thinking Mode']. Truncate the frontend literal to '⚡ Fast Mode' so the Gradio preprocess step accepts it.2c692a5 -
Fix gemma4 runtime error: switch to Transformers backend + Darwin-4B-David
Root cause: requirements.txt pinned transformers>=4.45.0 from PyPI, which has no gemma4 architecture. vLLM additionally lacks a Gemma4 model registration, so even a newer transformers would not have fixed the vLLM codepath. Result: all 3 engine-init tiers crashed with Value error, The checkpoint you are trying to load has model type gemma4 but Transformers does not recognize this architecture. Changes: - requirements.txt: drop vllm / aither-kvcache / optimum-quanto, install transformers @ git+https://github.com/huggingface/transformers.git (gemma4 is only present in the dev tree, unreleased). - app.py: remove vLLM LLMEngine / SamplingParams / TokensPrompt / TriAttention path. Load Gemma4ForConditionalGeneration directly with dtype=bfloat16, device_map=auto. Stream via TextIteratorStreamer in a background thread. Adapt MTILogitsProcessor to the Transformers LogitsProcessor API (batched entropy mask). Switch MODEL_ID to FINAL-Bench/Darwin-4B-David and point the tokeni…c8a5e69
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