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Mohammed Mohammed Ali

MohammedEltoum
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reacted to prithivMLmods's post with ๐Ÿ‘ 1 day ago
Dropping Downstream tasks using newly initialized parameters and weights ([classifier.bias & weights]) support domain-specific ๐—ถ๐—บ๐—ฎ๐—ด๐—ฒ ๐—ฐ๐—น๐—ฎ๐˜€๐˜€๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป. Based on siglip2-base-patch16-224 and DomainNet (single-domain, multi-source adaptation), with Fashion-MNIST for experimental testing. ๐Ÿงคโ˜„๏ธ Fashion-Mnist : https://huggingface.co/prithivMLmods/Fashion-Mnist-SigLIP2 Multisource-121 : https://huggingface.co/prithivMLmods/Multisource-121-DomainNet Painting-126 : https://huggingface.co/prithivMLmods/Painting-126-DomainNet Sketch-126 : https://huggingface.co/prithivMLmods/Sketch-126-DomainNet Clipart-126 : https://huggingface.co/prithivMLmods/Clipart-126-DomainNet Models are trained with different parameter settings for experimental purposes only, with the intent of further development. Refer to the model page below for instructions on running it with Transformers ๐Ÿค—. Collection : https://huggingface.co/collections/prithivMLmods/domainnet-0324-67e0e3c934c03cc40c6c8782 Citations : SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 & Moment Matching for Multi-Source Domain Adaptation : https://arxiv.org/pdf/1812.01754
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