Mxbai-large-v1 EmbedPress
Collection
Large datasets of mxbai-large-v1 embeddings with their truncated texts. Useful for distillation
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13 items
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Updated
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2
id
stringlengths 4
10
| text
stringlengths 18
1.2k
| embedding
list |
|---|---|---|
tc_0
|
Who was President when the first Peanuts cartoon was published?
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tc_1
|
Which American-born Sinclair won the Nobel Prize for Literature in 1930?
|
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tc_3
|
Where in England was Dame Judi Dench born?
|
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tc_4
|
William Christensen of Madison, New Jersey, has claimed to have the world's biggest collection of what?
|
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tc_5
|
In which decade did Billboard magazine first publish and American hit chart?
|
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tc_6
|
Where was horse racing's Breeders' Cup held in 1988?
|
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tc_8
|
From which country did Angola achieve independence in 1975?
|
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] |
tc_9
|
Which city does David Soul come from?
|
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tc_10
|
Who won Super Bowl XX?
|
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tc_11
|
Which was the first European country to abolish capital punishment?
|
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tc_12
|
What first appeared in Ohio in 1914 to affect transport?
|
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tc_14
|
In what field did the brother of the author of The Turn of the Screw find fame?
|
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tc_15
|
In which country did he widespread use of ISDN begin in 1988?
|
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Embedpress: mixedbread large on the TriviaQA queries dataset
This is the query portion of the TriviaQA dataset, embedded with Mixedbread AI's mixedbread-ai/mxbai-embed-large-v1. For each document, we take the first 510 tokens (the model's max length -2 special tokens), and embed it, not using any instructions. Because the model was trained using Matryoshka Representation Learning, these embeddings can safely be truncated.
These are mainly useful for large-scale knowledge distillation.
The dataset consists of 87k rows, each row has three keys:
id: the original id in the fineweb sampleembedding: The 1024-dimensional embeddingtext: The original text, truncated to the slice that was actually seen by the model
Because we truncate the original text, this can be directly used for training in, e.g., sentence-transformers, without having to worry about manually truncating text, matching etc.
Acknowledgments
Thanks Mixedbread AI for a GPU grant for research into small retrieval models.
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
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Number of rows:
87,622