twitter-xlm-roberta-base-sentiment-multilingual
cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual
Text Classificationtransformers
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 193.1K
- Total downloadsCumulative all-time download counter reported by the source platform.
- 11.6M
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +39.4K(increase)
- 0.3%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 33
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #41 among tracked Text Classification models.
- #1,568
- 20(down 20 places)this week
- Parameters
- —
- Last source update
- Mar 24, 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.
- 60.0
- twitter-xlm-roberta-base-sentiment-multilingual gained 39.4K downloads during the last seven tracked days.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
twitter-xlm-roberta-base-sentiment-multilingual is a text classification model published by cardiffnlp. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it Oct 6, 2026.
- Published
- Dec 1, 2022
- Last updated
- Mar 24, 2024
- Library
- transformers
- License
- —
- Task
- Text Classification
- Parameters
- —
- Spaces
- —
- Derivative models
- 1
- Velocity 7D/day
- 5,623
transformerspytorchxlm-robertatext-classificationdataset:cardiffnlp/tweet_sentiment_multilingualmodel-indextext-embeddings-inferenceendpoints_compatibleregion:usdeploy:azure
Model family
Based on base-model relationships reported by the source's metadata.
Derivative models
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