Update README.md

README.md

@@ -13,38 +13,33 @@ hf_oauth: true
 hf_oauth_scopes:
   - email
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-## 💎 Gemma 4 Playground — Dual Model Demo on ZeroGPU
-
-We just launched a **Gemma 4 Playground** that lets you chat with Google DeepMind's latest open models — directly on Hugging Face Spaces with ZeroGPU.
-
-**👉 Try it now:** [FINAL-Bench/Gemma-4-Multi](https://huggingface.co/spaces/FINAL-Bench/Gemma-4-Multi)
-
-### Two Models, One Space
 
+💎 Gemma 4 Playground — Dual Model Demo on ZeroGPU
+We just launched a Gemma 4 Playground that lets you chat with Google DeepMind's latest open models — directly on Hugging Face Spaces with ZeroGPU.
+👉 Try it now: FINAL-Bench/Gemma-4-Multi
+Two Models, One Space
 Switch between both Gemma 4 variants in a single interface:
 
-- **⚡ Gemma 4 26B-A4B** — MoE with 128 experts, only 3.8B active params. 95% of the 31B's quality at ~8x faster inference. AIME 88.3%, GPQA 82.3%.
-- **🏆 Gemma 4 31B** — Dense 30.7B. Best quality among Gemma 4 family. AIME 89.2%, GPQA 84.3%, Codeforces 2150. Arena open-model top 3.
-
-### Features
-
-- **Vision** — Upload images for analysis, OCR, chart reading, document parsing
-- **Thinking Mode** — Toggle chain-of-thought reasoning with Gemma 4's native `<|channel>` thinking tokens
-- **System Prompts** — 6 presets (General, Code, Math, Creative, Translate, Research) or write your own
-- **Streaming** — Real-time token-by-token response via ZeroGPU
-- **Apache 2.0** — Fully open, no restrictions
+⚡ Gemma 4 26B-A4B — MoE with 128 experts, only 3.8B active params. 95% of the 31B's quality at ~8x faster inference. AIME 88.3%, GPQA 82.3%.
+🏆 Gemma 4 31B — Dense 30.7B. Best quality among Gemma 4 family. AIME 89.2%, GPQA 84.3%, Codeforces 2150. Arena open-model top 3.
 
-### Technical Details
+Features
 
-Built with the dev build of `transformers` (5.5.0.dev0) for full Gemma 4 support including multimodal `apply_chat_template`, variable-resolution image processing, and native thinking mode. Runs on HF ZeroGPU with `@spaces.GPU` — no dedicated GPU needed.
+Vision — Upload images for analysis, OCR, chart reading, document parsing
+Thinking Mode — Toggle chain-of-thought reasoning with Gemma 4's native <|channel> thinking tokens
+System Prompts — 6 presets (General, Code, Math, Creative, Translate, Research) or write your own
+Streaming — Real-time token-by-token response via ZeroGPU
+Apache 2.0 — Fully open, no restrictions
 
+Technical Details
+Built with the dev build of transformers (5.5.0.dev0) for full Gemma 4 support including multimodal apply_chat_template, variable-resolution image processing, and native thinking mode. Runs on HF ZeroGPU with @spaces.GPU — no dedicated GPU needed.
 Both models support 256K context window and 140+ languages out of the box.
 
 ### Links
 
-- 🤗 **Space**: [FINAL-Bench/Gemma-4-Multi](https://huggingface.co/spaces/FINAL-Bench/Gemma-4-Multi)
-- 📄 **Gemma 4 26B-A4B**: [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it)
-- 📄 **Gemma 4 31B**: [google/gemma-4-31B-it](https://huggingface.co/google/gemma-4-31B-it)
-- 🔬 **DeepMind Blog**: [Gemma 4 Launch](https://deepmind.google/blog/gemma-4-byte-for-byte-the-most-capable-open-models/)
+- 🤗 Space: [FINAL-Bench/Gemma-4-Multi](https://huggingface.co/spaces/FINAL-Bench/Gemma-4-Multi)
+- 📄 Gemma 4 26B-A4B: [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it)
+- 📄 Gemma 4 31B: [google/gemma-4-31B-it](https://huggingface.co/google/gemma-4-31B-it)
+- 🔬 DeepMind Blog: [Gemma 4 Launch](https://deepmind.google/blog/gemma-4-byte-for-byte-the-most-capable-open-models/)
 
-Built by **VIDRAFT** 🧬
+Built by VIDRAFT 🧬