Mxbai-large-v1 EmbedPress
Collection
Large datasets of mxbai-large-v1 embeddings with their truncated texts. Useful for distillation • 13 items • Updated
• 2
id stringlengths 1 7 | text stringlengths 5 215 | embedding list |
|---|---|---|
1185869 | )what was the immediate impact of the success of the manhattan project? | [
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1185868 | _________ justice is designed to repair the harm to victim, the community and the offender caused by the offender criminal act. question 19 options: | [
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597651 | what color is amber urine | [
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403613 | is autoimmune hepatitis a bile acid synthesis disorder | [
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1183785 | elegxo meaning | [
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312651 | how much does an average person make for tutoring | [
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80385 | can you use a calculator on the compass test | [
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645590 | what does physical medicine do | [
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645337 | what does pending mean on listing | [
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186154 | feeding rice cereal how many times per day | [
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457407 | most dependable affordable cars | [
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441383 | lithophile definition | [
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683408 | what is a flail chest | [
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Embedpress: mixedbread large on the Msmarco queries dataset
This is the query portion of the MsMarco 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 509k 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:
1 GB
Size of the auto-converted Parquet files:
1 GB
Number of rows:
509,962