MoritzLaurer
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xlm-v-base-mnli-xnli

Zero-Shot Classification

text-classification

Inference Endpoints

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MoritzLaurer HF staff commited on Feb 9, 2023

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@@ -125,12 +125,12 @@ but XLM-V could be better on some languages based on its improved vocabulary.
 |Datasets|average|ar|bg|de|el|en|es|fr|hi|ru|sw|th|tr|ur|vi|zh|
 | :---:  | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |:---: |
 |Accuracy|0.780|0.757|0.808|0.796|0.79|0.856|0.814|0.806|0.751|0.782|0.725|0.757|0.766|0.729|0.784|0.782|
-|Speed (text/sec)|na|3501.0|3324.0|3438.0|3174.0|3713.0|3500.0|3129.0|3042.0|3419.0|3468.0|3782.0|3772.0|3099.0|3117.0|4217.0|
 |Datasets|mnli_m (en)|mnli_mm (en)|
 | :---: | :---: | :---: |
 |Accuracy|0.852|0.854|
-|Speed (text/sec)|2098.0|2170.0|
 ## Limitations and bias

 |Datasets|average|ar|bg|de|el|en|es|fr|hi|ru|sw|th|tr|ur|vi|zh|
 | :---:  | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |:---: |
 |Accuracy|0.780|0.757|0.808|0.796|0.79|0.856|0.814|0.806|0.751|0.782|0.725|0.757|0.766|0.729|0.784|0.782|
+|Speed GPU A100 (text/sec)|na|3501.0|3324.0|3438.0|3174.0|3713.0|3500.0|3129.0|3042.0|3419.0|3468.0|3782.0|3772.0|3099.0|3117.0|4217.0|
 |Datasets|mnli_m (en)|mnli_mm (en)|
 | :---: | :---: | :---: |
 |Accuracy|0.852|0.854|
+|Speed GPU A100 (text/sec)|2098.0|2170.0|
 ## Limitations and bias