wav2vec2-xlsr-53-ft-cy-en
techiaith/wav2vec2-xlsr-53-ft-cy-en
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 120
- Total downloadsCumulative all-time download counter reported by the source platform.
- 148K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +10(increase)
- 0.0%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 1
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #1500 among tracked Speech Recognition models.
- #53,544
- 478(up 478 places)this week
- Parameters
- 315M
- Last source update
- Aug 7, 2024
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 19.1
- wav2vec2-xlsr-53-ft-cy-en gained 10 downloads during the last seven tracked days.
- It moved from #1547 to #1500 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-xlsr-53-ft-cy-en is a speech recognition model published by techiaith. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it Oct 6, 2026.
- Published
- Oct 24, 2022
- Last updated
- Aug 7, 2024
- Library
- transformers
- License
- apache-2.0
- Task
- Speech Recognition
- Parameters
- 315,485,870
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 1
transformerssafetensorswav2vec2automatic-speech-recognitionspeechcyendataset:techiaith/banc-trawsgrifiadau-bangordataset:techiaith/commonvoice_16_1_en_cylicense:apache-2.0endpoints_compatibleregion:us
Publisher
techiaithView publisher statistics →Similar models
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