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reacted to SeaWolf-AI's post with 🔥 2 days ago
🖼️ POCKET-Image — the POCKET series goes visual: character-perfect text in any language, on-device A new model in VIDRAFT's POCKET family. POCKET put 35B-class models on phones and no-GPU PCs. POCKET-Image carries the same "big capability, small hardware" idea into image generation — and fixes the one thing nearly every image model gets wrong: text. Type "안녕하세요" into a typical model and you get "안ㅐ기." Hangul alone composes 11,172 syllable blocks; Arabic connects its letters; Thai stacks marks. Diffusion models draw scripts as shapes, so they smear. POCKET-Image renders every glyph exactly — 한국어 · 中文 · 日本語 · العربية (RTL) · ไทย · Latin and more — onto any scene you describe. What it is: • 100% accurate text, any language — where global models produce gibberish • Any background from a prompt — text is optional (empty → a pure image) • No GPU, no NPU — runs on plain CPU + RAM via the POCKET-Core engine • Measured footprint: 8.6 GB (RTX 3050/4060) · 4.5 GB (offloaded, 6 GB cards) · 13.4 GB (MacBook, 16 GB+) • Windows · macOS · Linux · fully local, no cloud Built on the open, commercial-friendly Z-Image (Apache-2.0) foundation. Honest note: the text is the guaranteed-correct part — the surrounding scene is ordinary generation, so a busy foreground can crowd the letters. We say so; clean backgrounds stay razor-sharp. 🎨 Studio — generate right here, any language: https://huggingface.co/spaces/FINAL-Bench/POCKET-Image-Studio 🧩 Model card: https://huggingface.co/FINAL-Bench/POCKET-Image-Zimage 📚 The POCKET collection: https://huggingface.co/collections/FINAL-Bench/pocket-models
reacted to SeaWolf-AI's post with ❤️ 2 days ago
🖼️ POCKET-Image — the POCKET series goes visual: character-perfect text in any language, on-device A new model in VIDRAFT's POCKET family. POCKET put 35B-class models on phones and no-GPU PCs. POCKET-Image carries the same "big capability, small hardware" idea into image generation — and fixes the one thing nearly every image model gets wrong: text. Type "안녕하세요" into a typical model and you get "안ㅐ기." Hangul alone composes 11,172 syllable blocks; Arabic connects its letters; Thai stacks marks. Diffusion models draw scripts as shapes, so they smear. POCKET-Image renders every glyph exactly — 한국어 · 中文 · 日本語 · العربية (RTL) · ไทย · Latin and more — onto any scene you describe. What it is: • 100% accurate text, any language — where global models produce gibberish • Any background from a prompt — text is optional (empty → a pure image) • No GPU, no NPU — runs on plain CPU + RAM via the POCKET-Core engine • Measured footprint: 8.6 GB (RTX 3050/4060) · 4.5 GB (offloaded, 6 GB cards) · 13.4 GB (MacBook, 16 GB+) • Windows · macOS · Linux · fully local, no cloud Built on the open, commercial-friendly Z-Image (Apache-2.0) foundation. Honest note: the text is the guaranteed-correct part — the surrounding scene is ordinary generation, so a busy foreground can crowd the letters. We say so; clean backgrounds stay razor-sharp. 🎨 Studio — generate right here, any language: https://huggingface.co/spaces/FINAL-Bench/POCKET-Image-Studio 🧩 Model card: https://huggingface.co/FINAL-Bench/POCKET-Image-Zimage 📚 The POCKET collection: https://huggingface.co/collections/FINAL-Bench/pocket-models
reacted to SeaWolf-AI's post with 👍 2 days ago
🖼️ POCKET-Image — the POCKET series goes visual: character-perfect text in any language, on-device A new model in VIDRAFT's POCKET family. POCKET put 35B-class models on phones and no-GPU PCs. POCKET-Image carries the same "big capability, small hardware" idea into image generation — and fixes the one thing nearly every image model gets wrong: text. Type "안녕하세요" into a typical model and you get "안ㅐ기." Hangul alone composes 11,172 syllable blocks; Arabic connects its letters; Thai stacks marks. Diffusion models draw scripts as shapes, so they smear. POCKET-Image renders every glyph exactly — 한국어 · 中文 · 日本語 · العربية (RTL) · ไทย · Latin and more — onto any scene you describe. What it is: • 100% accurate text, any language — where global models produce gibberish • Any background from a prompt — text is optional (empty → a pure image) • No GPU, no NPU — runs on plain CPU + RAM via the POCKET-Core engine • Measured footprint: 8.6 GB (RTX 3050/4060) · 4.5 GB (offloaded, 6 GB cards) · 13.4 GB (MacBook, 16 GB+) • Windows · macOS · Linux · fully local, no cloud Built on the open, commercial-friendly Z-Image (Apache-2.0) foundation. Honest note: the text is the guaranteed-correct part — the surrounding scene is ordinary generation, so a busy foreground can crowd the letters. We say so; clean backgrounds stay razor-sharp. 🎨 Studio — generate right here, any language: https://huggingface.co/spaces/FINAL-Bench/POCKET-Image-Studio 🧩 Model card: https://huggingface.co/FINAL-Bench/POCKET-Image-Zimage 📚 The POCKET collection: https://huggingface.co/collections/FINAL-Bench/pocket-models
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