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Source channel @githubtrending · Post #14627 · Apr 24

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#jupyter_notebook DINOv2 is a powerful AI model from Meta AI that learns to understand images without needing labeled data, using self-supervised learning. It was trained on 142 million images and creates strong visual features that work well for many tasks like image classification, depth estimation, and segmentation without extra fine-tuning. You can use its pretrained models easily with simple classifiers, saving time and effort. DINOv2 is efficient, scalable, and performs better than many other models, making it great for building versatile computer vision applications quickly and accurately. It’s open-source and ready to use with PyTorch. https://github.com/facebookresearch/dinov2

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Ali Ahmad

@AlisherAhmatovich · Post #1189 · 01/09/2025, 04:15 PM

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O'zbekcha STT (Speech-to-Text) uchun benchmarking v1 tayyor! O'zbek tilida nutqni matnga aylantirish bo'yicha dastlabki etalon tizimni yaratdik! Ushbu jarayonda: ✅ Adabiy O'zbek tili ✅ Turli hududiy shevalar ✅ Musiqalar va suhbatlar ✅ Shovqinli audiolar bilan o’zimizni va bozordagi mavjud modellarni sinab ko'rdik. Tez orada natijalarni va benchmarkni e’lon qilamiz, hamda benchmarkni doimiy yangilab borish niyatimiz bor. Benchmark mezonlari: - WER (Word Error Rate) - So’zlar xatolik darajasi. - CER (Character Error Rate) – Harflar xatolik darajasi. Bu nafaqat texnologik rivojlanish, balki O'zbek tilining raqamli muhitda mustahkam o'rin egallashi yo'lida muhim qadamdir. Maqsadimiz – O'zbekcha STT modellarining aniq va sifatli ishlashini ta'minlashdir. Kelajak rejalari: - Test natijalarini batafsil tahlil qilib, modellarni yanada takomillashtirish. O'zbek tili texnologiyalari rivoji uchun birgalikda ishlashda davom etamiz! STT modelimizni @aishaovozbot’da yoki aisha.group’da sinab ko’rishingiz mumkin. #aisha#stt @elzodxon

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