GTE modernbert Embedpress
Collection
A bunch of datasets embedded with GTE modernbert. Sponsored by Mixedbread AI • 14 items • Updated
text stringlengths 0 370 | embedding list |
|---|---|
What was Achilles' fate? | [
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Who was the first to give Aristotle the title of "First Teacher"? | [
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What did Franz Boas publicly object to? | [
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What is the name of the committee that made other changes to ASCII? | [
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What is the Amphibian Conservation Action Plan? | [
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What is the largest river delta in the world? | [
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What are the issues suitable for appeal in criminal cases? | [
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What are the functions of Suanpan? | [
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What is the thermal resistance of adobe? | [
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How many radio stations does Afghanistan have? | [
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What is the conclusion of archaeologists about the Bronze Age artefacts from tumulus burials? | [
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What are the major parts of Azerbaijanis culture? | [
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What were the four stable power blocs in the Hellenistic world? | [
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Embedpress: Alibaba-NLP/gte-modernbert-base on the nthakur/swim-ir-monolingual dataset
This is the nthakur/swim-ir-monolingual 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
text(string) — the query text used for embeddingembedding(float32[768]) — the vector representation fromAlibaba-NLP/gte-modernbert-base
Split
train— 501538 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
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Size of downloaded dataset files:
1.57 GB
Size of the auto-converted Parquet files:
1.57 GB
Number of rows:
501,538