mlcommons / mlcommons/endpoints

MATH500 - Dataset integration

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area: dataset area: evaluation priority: P1 type: feature
Dominant language
Python
Stars
21
Forks
28
Avg merge
3d 17h
Merged PRs (30d)
13

Description

Can reuse existing BoxedMathExtractor

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the existing BoxedMathExtractor and the repository's dataset integration entry points. Determine how MATH500 should be represented and wired in; done means the dataset is integrated using the existing extractor, with the relevant validation or tests passing.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data, machine-learning
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
35/100

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