msmarco

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Published: Apr 16, 2026 License: Apache-2.0 Imports: 0 Imported by: 0

README

MSMARCO Dataset

Used to evaluating ranking and retrieval models.

This package contains a pre-generated schema (and the //go:generate line that does that) and some tests to demo it.

For more information see:

benchmark_embed

It includes this small binary that will attempt to embed all the MSMARCO passages using the given model, and print out the speed. It simply discards the embeddings.

It's provides 3 functionalities:

  • Check that a model works.
  • Benchmark it in any supporting backend.
  • Example for someone who needs to do something similar.

It only embeds the passages, because generally the "document" doesn't require any instruction, while queries usually require instructions, and there is not a general way to specify them.

Documentation

Index

Constants

View Source
const (
	ID              = "microsoft/ms_marco"
	Config          = "v2.1"
	TrainSplit      = "train"
	TestSplit       = "test"
	ValidationSplit = "validation"
)

Variables

This section is empty.

Functions

This section is empty.

Types

type MsMarcoRecord

type MsMarcoRecord struct {
	Answers           []string     `json:"answers" parquet:"answers,list"`
	Passages          PassagesItem `json:"passages" parquet:"passages"`
	Query             string       `json:"query" parquet:"query"`
	QueryID           int32        `json:"query_id" parquet:"query_id"`
	QueryType         string       `json:"query_type" parquet:"query_type"`
	WellFormedAnswers []string     `json:"wellFormedAnswers" parquet:"wellFormedAnswers,list"`
}

type PassagesItem

type PassagesItem struct {
	IsSelected  []int32  `json:"is_selected" parquet:"is_selected,list"`
	PassageText []string `json:"passage_text" parquet:"passage_text,list"`
	URL         []string `json:"url" parquet:"url,list"`
}

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