multi-label-class-classification-on-github-issues
Rami/multi-label-class-classification-on-github-issues
Text Classificationtransformers
Tracked by OpenModelStats since September 8, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 3,381
- Total downloadsCumulative all-time download counter reported by the source platform.
- 80.1K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +1,058(increase)
- 1.4%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 4
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #426 among tracked Text Classification models.
- #14,424
- 233(down 233 places)this week
- Parameters
- —
- Last source update
- Jan 11, 2023
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 54.9
- multi-label-class-classification-on-github-issues gained 1,058 downloads during the last seven tracked days.
- It moved from #421 to #426 among tracked Text Classification models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
multi-label-class-classification-on-github-issues is a text classification model published by Rami. OpenModelStats has tracked the model since Sep 8, 2026, most recently observing it 18h ago.
- Published
- Dec 1, 2022
- Last updated
- Jan 11, 2023
- Library
- transformers
- License
- —
- Task
- Text Classification
- Parameters
- —
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 151
transformerspytorchtensorboardberttext-classificationgenerated_from_trainertext-embeddings-inferenceendpoints_compatibleregion:us
Publisher
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