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isaac-chung
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Feb 26, 2026
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Overall looks good. One small thing, and how would this be tested?
| """ | ||
| meta = get_model_meta(model_name, revision).model_copy(deep=True) | ||
| model = meta.load_model(device=device, **kwargs) | ||
| model = meta.load_model(device=device, embed_dim=embed_dim, **kwargs) |
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What do you think about letting embed_dim be part of kwargs?
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I've added it to args of get_model for more visibility of this feature
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This pull request has been automatically marked as stale due to inactivity. |
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Ah great addition! Can the following tests:
- Ensure that it works with experiments
- ensure that the metadata saves when running a model corresponds to the embedding dimension used. Currently I think it will save a list
| array_framework: Literal["numpy", "torch"] = "numpy", | ||
| dtype: torch.dtype | np.floating = np.float32, | ||
| embed_dim: int = _EMBEDDING_DIM, | ||
| embed_dim: int | None = None, |
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Why the change here?
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To match with SentenceTransformerWrapper
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Close #2832
Add Matryoshka support. Extended
ModelMeta.embedding_dimto support list for different embedding dimensions. Example: