tiny-random-LlamaForCausalLM
hmellor/tiny-random-LlamaForCausalLM
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 2.5M
- Total downloadsCumulative all-time download counter reported by the source platform.
- 25.1M
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
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- 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.
- 2
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #33 among tracked Text Generation models.
- #156
- 44(down 44 places)this week
- Parameters
- 1.1M
- Last source update
- Apr 29, 2025
- It moved from #28 to #33 among tracked Text Generation models this week.
Downloads over time
Rolling recent-window downloads as reportedNot 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
tiny-random-LlamaForCausalLM is a text generation model published by hmellor. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 58 min ago.
- Published
- Apr 29, 2025
- Last updated
- Apr 29, 2025
- Library
- transformers
- License
- —
- Task
- Text Generation
- Parameters
- 1,062,992
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
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transformerssafetensorsllamatext-generationconversationalarxiv:1910.09700text-generation-inferenceendpoints_compatibleregion:us
Publisher
hmellorView publisher statistics →Similar models
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