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YoungMin

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reacted to SeaWolf-AI's post with 🔥 about 4 hours ago
💎 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. https://huggingface.co/spaces/FINAL-Bench/Gemma-4-Multi 👉 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 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/)
reacted to SeaWolf-AI's post with 🚀 about 4 hours ago
💎 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. https://huggingface.co/spaces/FINAL-Bench/Gemma-4-Multi 👉 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 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/)
reacted to SeaWolf-AI's post with 👍 about 4 hours ago
💎 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. https://huggingface.co/spaces/FINAL-Bench/Gemma-4-Multi 👉 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 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/)
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