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Training Wan 2.1-1.3B to use Qwen3-VL-2B text encoder. Doing 33% text only, 33% VL only, and 33% both. Just pretraining the two text input linear layers for now. It is amazing how quickly a model can adapt to a different text encoder. This is 25,750 steps, BS of 10.

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Ostris

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26,778 просмотров • 4 месяцев назад •via X (Twitter)

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A quick way to improve how text behaves in your app is to use `text-wrap: balance`. It distributes text evenly across each line, avoiding orphaned words. It is only supported for a limited number lines (<6-10 depending on the browser), which means it's best used for headings or short paragraphs.
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A quick way to improve how text behaves in your app is to use `text-wrap: balance`. It distributes text evenly across each line, avoiding orphaned words. It is only supported for a limited number lines (<6-10 depending on the browser), which means it's best used for headings or short paragraphs.

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Bismillah. Image-To-Text Converter for Non-English PDFs is now available! It converts books in Arabic, Urdu, Persian, Spanish, etc. with amazing accuracy Currently this just a MVP version that extracts text but there is a lot on the roadmap iA Link below to test it out!

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