mlcommons / mlcommons/modelbench
Split v1 Benchmark by language
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- Dominant language
- Python
- Stars
- 134
- Forks
- 36
- Avg merge
- 1d 11h
- Merged PRs (30d)
- 17
Description
class Locale(str, Enum):
EN_US = "EN_US" # English, United States
FR_FR = "FR_FR" # French, France
ZH_CN = "ZH_CN" # Simplified Chinese, China
HI_IN = "HI_HI" # Hindi, India
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the v1 benchmark entry point and the Locale enum shown in the issue. Trace how benchmark results are grouped, then determine how language-specific runs should be separated and reported. Done means the v1 benchmark is split by the listed languages, with coverage for each language-specific path.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100