Political_DEBATE_base_v1.0
mlburnham/Political_DEBATE_base_v1.0
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 443
- Total downloadsCumulative all-time download counter reported by the source platform.
- 8,242
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- —
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 9
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #80 among tracked Zero-Shot Classification models.
- #28,273
- –this week
- Parameters
- 184M
- Last source update
- Dec 13, 2024
Downloads over time
Cumulative total downloads observed by OpenModelStatsNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Likes over time
Not enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Rank among tracked models
Lower is betterNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Overview
Political_DEBATE_base_v1.0 is a zero-shot classification model published by mlburnham. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 4h ago.
- Published
- Aug 16, 2024
- Last updated
- Dec 13, 2024
- Library
- transformers
- License
- mit
- Task
- Zero-Shot Classification
- Parameters
- 184,423,682
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
transformerssafetensorsdeberta-v2text-classificationPoliticsTopic ClassificationHate SpeechOpinion MiningEvent Extractionzero-shot-classificationendataset:mlburnham/Pol_NLI
Publisher
mlburnhamView publisher statistics →Similar models
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