MediPhi-Instruct
microsoft/MediPhi-Instruct
Tracked by OpenModelStats since September 7, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 1,547
- Total downloadsCumulative all-time download counter reported by the source platform.
- 51K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +222(increase)
- 0.5%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 70
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #7354 among tracked Text Generation models.
- #28,386
- 316(down 316 places)this week
- Parameters
- 3.8B
- Last source update
- Dec 15, 2025
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 37.7
- MediPhi-Instruct gained 222 downloads during the last seven tracked days.
- It moved from #7284 to #7354 among tracked Text Generation models this week.
Downloads over time
Rolling recent-window downloads as reportedLikes over time
Rank among tracked models
Lower is betterOverview
MediPhi-Instruct is a text generation model published by microsoft. OpenModelStats has tracked the model since Sep 7, 2026, most recently observing it Oct 7, 2026.
- Published
- Jul 11, 2025
- Last updated
- Dec 15, 2025
- Library
- transformers
- License
- mit
- Task
- Text Generation
- Parameters
- 3,821,079,552
- Spaces
- —
- Derivative models
- 1
- Velocity 7D/day
- 32
transformerssafetensorsphi3text-generationmergemergekitmedicalclinicalconversationalendataset:microsoft/mediflowdataset:ncbi/pubmed
Publisher
microsoftView publisher statistics →Derived from microsoft/Phi-3.5-mini-instruct (reported by the source; parent not yet tracked).
Model family
Based on base-model relationships reported by the source's metadata.
Derivative models
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