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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what does chattel mean on credit history
|
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what was the great leap forward brainly
|
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tattoo fixers how much does it cost
|
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] |
what is decentralization process.
|
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] |
how many cars enter the la jolla concours d' elegance?
|
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] |
what is a bank transit number
|
[
0.38707903027534485,
1.6410294771194458,
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] |
how much can i contribute to nondeductible ira
|
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] |
what are the four major groups of elements
|
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] |
blood clots in urine after menopause
|
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] |
per sf cost in california for tenant build out
|
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End of preview. Expand
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Embedpress: Alibaba-NLP/gte-modernbert-base on the sentence-transformers/msmarco-corpus dataset
This is the sentence-transformers/msmarco-corpus 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— 1010916 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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Size of downloaded dataset files:
3.16 GB
Size of the auto-converted Parquet files:
3.16 GB
Number of rows:
1,010,916