acquisition_student_AS_confidence_medmcqa_qwen7b
ishikaa/acquisition_student_AS_confidence_medmcqa_qwen7b
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 423
- Total downloadsCumulative all-time download counter reported by the source platform.
- 423
- 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.
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- LikesCommunity likes reported by the source platform.
- 0
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #7759 among tracked Text Generation models.
- #28,470
- –this week
- Parameters
- 7.6B
- Last source update
- Aug 23, 2026
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
acquisition_student_AS_confidence_medmcqa_qwen7b is a text generation model published by ishikaa. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 11h ago.
- Published
- Aug 22, 2026
- Last updated
- Aug 23, 2026
- Library
- transformers
- License
- —
- Task
- Text Generation
- Parameters
- 7,615,616,512
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
transformerssafetensorsqwen2text-generationtrlsftconversationalarxiv:1910.09700text-generation-inferenceendpoints_compatibleregion:us
Publisher
ishikaaView publisher statistics →Similar models
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