CLIP ViT base-patch32 · SMAT · SVHN

A SMAT expert from Table 2 of SMAT: Simple and Efficient Merge-Aware Training (seed 42). SMAT trains experts with model merging in mind.

Paper · GitHub & usage

encoder.pt is the original FP32 vision-encoder state dictionary; load it with the SMAT code and the matching OpenAI CLIP base model. Dataset terms apply separately.

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Collection including yanggangu/CLIP-ViT-base-patch32-SMAT-SVHN

SMAT: Simple and Efficient Merge-Aware Training

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Paper, FT/SMAT experts and frozen datasets for Tables 1 and 2. • 63 items • Updated 20 days ago

Paper for yanggangu/CLIP-ViT-base-patch32-SMAT-SVHN

SMAT: Simple and Efficient Merge-Aware Training

Paper • 2609.33437 • Published 23 days ago • 5