GTE modernbert Embedpress
Collection
A bunch of datasets embedded with GTE modernbert. Sponsored by Mixedbread AI
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14 items
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Updated
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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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0.216887965798378,
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1.0869871377944946,
-1.3485071659088135
] |
When does Menopause start?
|
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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.
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Number of rows:
3,547