@MrStickman

Aligner (Bitext Align): free word-by-word translation visualizer. Stack multiple lines, link adjacent rows in the preview, optional gloss/IPA lines, exports (PNG, SVG, PDF, HTML), and shareable URLs. For learners, teachers, linguists, and conlang posts.

As of today, June 5, 2026, we have deprecated the following models across most GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions). Note…

Die Legende ist zurück – Reise in diesem originalgetreuen Remake des klassischen genreprägenden Rollenspiels erneut durch das Minental. Erkunde eine von Hand erschaffene, organische, offene und raue Welt, die dynamisch und unvergleichlich auf deine Aktionen reagiert.

From TF's website: Quantization aware training emulates inference-time quantization, creating a model that downstream tools will use to produce actually quantized models. So is it designed to work with a very specific quantization method (for Gemma-4, presumably, Google's own)? Or would it make sense to use alternative quantization methods? According to the benchmarks unsloth released, its (alternative) quantizations of Gemma-4-QAT are closer to the QAT fine-tunes, but is it a good thing, or does it defeat the purpose of QAT? submitted by /u/we_are_mammals [link] [Kommentare]