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Add giga embeddings #1741

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Add giga embeddings #1741

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Samoed
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@Samoed Samoed commented Jan 9, 2025

Added InstructSentenceTransformerWrapper to use SentenceTransforme models with instructions.

Ref embeddings-benchmark/results#77
@ekolodin My results are a bit higher. Could you rerun your results using this implementation, or provide your implementation? My code for run

Checklist

  • Run tests locally to make sure nothing is broken using make test.
  • Run the formatter to format the code using make lint.

Adding a model checklist

  • I have filled out the ModelMeta object to the extent possible
  • I have ensured that my model can be loaded using
    • mteb.get_model(model_name, revision) and
    • mteb.get_model_meta(model_name, revision)
  • I have tested the implementation works on a representative set of tasks.
Task Leaderboard PR
AmazonCounterfactualClassification 90.31 94.1493
EmotionClassification 73.1 92.075
ToxicConversationsClassification 75.37 90.1123
SprintDuplicateQuestions 86.3 93.487
TwitterSemEval2015 63.42 65.8234
SciDocsRR 88.01 84.5092
AskUbuntuDupQuestions 58.19 61.41
SCIDOCS 19.16 20.056
SciFact 72.9 67.707
STS16 81.09 79.6737
STSBenchmark 82.2 78.9945
SummEval 27.86 30.9884

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@KennethEnevoldsen KennethEnevoldsen left a comment

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I would appreciate the metadata add but otherwise it looks good. Of course lets wait until we have a look at the differences in score.

Comment on lines +268 to +269
use_instructions=True,
)
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Can we add the training data annotation as well (we are going through models and adding that)

see_ #1561

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They haven't publish report yet, so I don't know anything about training dataset

Comment on lines +127 to +133
# to passage prompts won't be applied to passages
if (
not self.apply_instruction_to_passages
and prompt_type == PromptType.passage
and task.metadata.type == "s2p"
):
instruction = None
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Why?

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Similar to jasper and nv-embed this model doesn't use prompt for passages. I think that can be helpful to add this to base class

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2 participants