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serengeti-E250

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Transformers
PyTorch
26 languages
electra
feature-extraction
Masked Langauge Model
Inference Endpoints
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  ```
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  ## Acknowledgments
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- We gratefully acknowledges support from Canada Research Chairs (CRC), the Natural Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2018-04267), the Social Sciences and Humanities Research Council of Canada (SSHRC; 435-2018-0576; 895-2020-1004; 895-2021-1008), Canadian Foundation for Innovation (CFI; 37771), [Digital Research Alliance of Canada](https://alliancecan.ca), [UBC ARC-Sockeye](https://arc.ubc.ca/ubc-arc-sockeye), Advanced Micro Devices, Inc. (AMD), and Google. Any opinions, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of CRC, NSERC, SSHRC, CFI, the Alliance, AMD, Google, or UBC ARC-Sockeye.
 
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  ```
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  ## Acknowledgments
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+ We gratefully acknowledges support from Canada Research Chairs (CRC), the Natural Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2018-04267), the Social Sciences and Humanities Research Council of Canada (SSHRC; 435-2018-0576; 895-2020-1004; 895-2021-1008), Canadian Foundation for Innovation (CFI; 37771), [Digital Research Alliance of Canada](https://alliancecan.ca), [UBC ARC-Sockeye](https://arc.ubc.ca/ubc-arc-sockeye), Advanced Micro Devices, Inc. (AMD), and Google. Any opinions, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of CRC, NSERC, SSHRC, CFI, the Alliance, AMD, Google, or UBC ARC-Sockeye.