Mithil-AI
/

quadembed-nano

Feature Extraction

sentence-similarity

image-text-retrieval

contrastive-learning

jina-embeddings

Model card Files Files and versions

Mithil Maske commited on 9 days ago

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8ac1fab

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1 Parent(s): 544e32b

Link the now-live GitHub repo

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@@ -80,7 +80,8 @@ capacity). Short version: architecture wasn't the bottleneck after round 3;
 raw training data volume was — R@1 only moved once the image-caption
 training set was scaled to ~172k pairs (round 7). The full round-by-round
 write-up, with what did and didn't move the needle, lives in the source
-repo's README and feasibility notes (linked once published).
 ## Usage

 raw training data volume was — R@1 only moved once the image-caption
 training set was scaled to ~172k pairs (round 7). The full round-by-round
 write-up, with what did and didn't move the needle, lives in the source
+repo's README and feasibility notes:
+[github.com/mithilai/QuadEmbed](https://github.com/mithilai/QuadEmbed).
 ## Usage