Adds gemma3 embedding support#209
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(cherry picked from commit 3095231)
(cherry picked from commit 056c4a6)
- Cleaned up gemma3.py by removing commented-out code related to HuggingFace token. - Updated the token placeholder in bert.rs to reflect the correct usage of "hf_key". - Minor adjustments in gemma3.rs to remove unnecessary code for clarity. (cherry picked from commit 2b3c8da)
The dev merge reworked EmbeddingModel.from_pretrained_hf to drop the WhichModel argument and auto-detect the architecture from config.json (Gemma3TextModel). Update the example call to the new signature. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- Add 768→3072→768 dense projection head between mean-pool and L2-norm - Switch the transformer to bidirectional attention with a padding mask - Apply per-layer RoPE: local base freq for sliding layers, global for full-attention layers - Add golden test against sentence-transformers output verified to ~1e-6
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Adds gemma3 embedding support.
Completed work started from #173. I cherry-picked commits from the referenced branch into this branch, and authored w/ Claude the completed implementation. I pulled embeddinggemma from HF and generated golden vectors from sentence-transformers. You will find tests checking the first 6 dims of those vectors as per what appears to be custom in the rest of the repo.