GTE modernbert Embedpress
Collection
A bunch of datasets embedded with GTE modernbert. Sponsored by Mixedbread AI • 14 items • Updated
text stringlengths 11 129 | embedding list |
|---|---|
Was there a year 0? | [
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When is the dialectical method used? | [
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What do Grasshoppers eat? | [
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How large is the Kerman province of southeastern Iran? | [
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When was the USS Taylor built? | [
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What's the difference between man-slaughter and homicide? | [
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When was special relativity developed? | [
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Who was the last Han Dynasty Emperor? | [
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When did Iain M. Banks create The Culture? | [
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What is the population of emperor penguins in Antarctica? | [
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Who started human rights? | [
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Who is the Mayor of San Francisco? | [
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When does Menopause start? | [
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... |
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in Data Studio
Embedpress: Alibaba-NLP/gte-modernbert-base on the sentence-transformers/mr-tydi dataset
This is the sentence-transformers/mr-tydi dataset, embedded with Alibaba-NLP/gte-modernbert-base.
For each example, we embed the text directly (no additional instruction prompt). Embeddings have dimensionality 768.
These embeddings are intended for tasks like large-scale distillation, retrieval, and similarity search. Because the raw text may exceed the model’s limit, we recommend truncating to the model’s maximum token length at build time.
Schema
id(string) — unique identifiertext(string) — the query text used for embeddingembedding(float32[768]) — the vector representation fromAlibaba-NLP/gte-modernbert-base
Split
train— 3547 examples
Notes
- Produced with
Alibaba-NLP/gte-modernbert-basefrom Hugging Face Hub. - If you need a smaller embedding size (e.g., matryoshka/truncated vectors), you can safely slice the embeddings without re-embedding.
Acknowledgments
Thanks Mixedbread AI for a GPU grant for research into small retrieval models.
- Downloads last month
- 7
Size of downloaded dataset files:
11.6 MB
Size of the auto-converted Parquet files:
11.6 MB
Number of rows:
3,547