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reacted to mitkox's post with 👀 about 1 month ago
I see all Chinese labs are turning TL;DR into TL;DRGB Problem: 1M text tokens == 1 M opportunities for your GPU to file worker-comp Solution: don’t feed the model War & Peace—feed it the movie poster. This is Glyph, Zai’s new visual-text compression voodoo: • 10 k words → 3 PNGs ≈ 3 k visual tokens • Compression ratio: 4.3× • Throughput: 40-60 tok/s i.e. your context window now finishes before my coffee does So I did the only reasonable thing: asked GLM-4.6 to port Glyph for Qwen3-VL-8B-Thinking. Translation: I made one model compress a novel into a comic strip, then made another model read the comic strip and still ace QA. It’s basically passing notes in class, except the note is a 1920×1080 meme and the teacher is a transformer. We've gone from "Attention is All You Need" to "Attention is Too Expensive, Just Use Your Eyes." Remember kids: in 2025 literacy is optional, but JPEG is forever.
new activity 2 months ago
openbmb/VoxCPM-Demo:I believe the model works best when processed sentence by sentence
new activity 2 months ago
openbmb/VoxCPM-0.5B:Mac mps support?
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