wav2vec2-xlsr-japanese-speech-emotion-recognition
Bagus/wav2vec2-xlsr-japanese-speech-emotion-recognition
Tracked by OpenModelStats since September 7, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 1,556
- Total downloadsCumulative all-time download counter reported by the source platform.
- 25.9K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +608(increase)
- 2.5%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 5
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #94 among tracked Audio Classification models.
- #26,500
- 255(down 255 places)this week
- Parameters
- 316M
- Last source update
- Oct 19, 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.
- 53.4
- wav2vec2-xlsr-japanese-speech-emotion-recognition gained 608 downloads during the last seven tracked days.
- It moved from #92 to #94 among tracked Audio Classification models this week.
Downloads over time
Rolling recent-window downloads as reportedLikes over time
Rank among tracked models
Lower is betterOverview
wav2vec2-xlsr-japanese-speech-emotion-recognition is a audio classification model published by Bagus. OpenModelStats has tracked the model since Sep 7, 2026, most recently observing it 30h ago.
- Published
- Mar 2, 2022
- Last updated
- Oct 19, 2023
- Library
- transformers
- License
- —
- Task
- Audio Classification
- Parameters
- 316,492,420
- Spaces
- 1
- Derivative models
- —
- Velocity 7D/day
- 87
transformerspytorchsafetensorswav2vec2audio-classificationaudiospeechspeech-emotion-recognitionjadataset:jtesendpoints_compatibleregion:us
Publisher
BagusView publisher statistics →Similar models
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