UBC-NLP
/

serengeti-E250

feature-extraction

Masked Langauge Model

Inference Endpoints

Model card Files Files and versions Community

Ife commited on Oct 18, 2023

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 <p align="center">
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-    <img src="./images/serengeti_logo.png"/>
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-<img src="./images/serengati_languages.jpg" width="50%" height="50%" align="right">
 <div style='text-align: justify;'>
 Multilingual pretrained language models (mPLMs) acquire valuable, generalizable linguistic information during pretraining and have advanced the state of the art on task-specific finetuning.
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 <p align="center">
     <br>
+    <img src="./serengeti_logo.png"/>
     <br>
 <p>
 </p>
+<img src="./serengati_languages.jpg" width="50%" height="50%" align="right">
 <div style='text-align: justify;'>
 Multilingual pretrained language models (mPLMs) acquire valuable, generalizable linguistic information during pretraining and have advanced the state of the art on task-specific finetuning.
 <br><br>