
This is a [MicroBERT](https://github.com/lgessler/microbert) model for Coptic.

* Its suffix is **-mx**, which means that it was pretrained using supervision from masked language modeling and XPOS tagging.
* The unlabeled Coptic data was taken from version 4.2.0 of the [Coptic SCRIPTORIUM corpus](https://github.com/copticscriptorium/corpora), totaling 970,642 tokens. 
* The UD treebank [UD_Coptic_Scriptorium](https://github.com/UniversalDependencies/UD_Coptic-Scriptorium), v2.9, totaling 48,632 tokens, was used for labeled data.

Please see [the repository](https://github.com/lgessler/microbert) and 
[the paper](https://github.com/lgessler/microbert/raw/master/MicroBERT__MRL_2022_.pdf) for more details.
{"language": "cop", "widget": [{"text": "\u2c81\u2c97\u2c97\u2c81 \u2c81\u2c9b\u2c9f\u2c95 \u2c81\u2c93\u2ca5\u2c89\u2ca7\u2ca1\u2ca7\u2c8f\u2ca9\u2ca7\u2c9b \u00b7"}]}
transformers pytorch bert feature-extraction cop endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #feature-extraction #cop #endpoints_compatible #region-us 


This is a MicroBERT model for Coptic.

* Its suffix is -mx, which means that it was pretrained using supervision from masked language modeling and XPOS tagging.
* The unlabeled Coptic data was taken from version 4.2.0 of the Coptic SCRIPTORIUM corpus, totaling 970,642 tokens. 
* The UD treebank UD_Coptic_Scriptorium, v2.9, totaling 48,632 tokens, was used for labeled data.

Please see the repository and 
the paper for more details.
TAGS
#transformers #pytorch #bert #feature-extraction #cop #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #feature-extraction #cop #endpoints_compatible #region-us 
