mlcommons / mlcommons/modelbench
Json run output includes detailed success/failure
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Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 134
- Forks
- 36
- Avg merge
- 1d 11h
- Merged PRs (30d)
- 17
Description
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Contributor guide
First steps
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Research direction
The issue body does not identify files, tests, or an entry point. Start by locating where benchmark run results are serialized as JSON, then determine which detailed success and failure information the output should include and verify the resulting JSON against the expected run outcomes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- cli
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100