wav2vec2-large-xlsr-53-esperanto
cpierse/wav2vec2-large-xlsr-53-esperanto
Tracked by OpenModelStats since October 1, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 2,003
- Total downloadsCumulative all-time download counter reported by the source platform.
- 1.2M
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +724(increase)
- 0.1%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 7
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #590 among tracked Speech Recognition models.
- #22,462
- 268(up 268 places)this week
- Parameters
- 315M
- Last source update
- Jul 31, 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.
- 45.6
- wav2vec2-large-xlsr-53-esperanto gained 724 downloads during the last seven tracked days.
- It moved from #591 to #590 among tracked Speech Recognition models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
wav2vec2-large-xlsr-53-esperanto is a speech recognition model published by cpierse. OpenModelStats has tracked the model since Oct 1, 2026, most recently observing it 3h ago.
- Published
- Mar 2, 2022
- Last updated
- Jul 31, 2023
- Library
- transformers
- License
- apache-2.0
- Task
- Speech Recognition
- Parameters
- 315,483,820
- Spaces
- —
- Derivative models
- 1
- Velocity 7D/day
- 103
transformerspytorchjaxsafetensorswav2vec2automatic-speech-recognitionaudiospeechxlsr-fine-tuning-weekeodataset:common_voicelicense:apache-2.0
Publisher
cpierseView publisher statistics →Model family
Based on base-model relationships reported by the source's metadata.
Derivative models
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