Update README.md

README.md

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 license: cc-by-sa-4.0
+library_name: transformers
+pipeline_tag: text-classification
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 ### xlm-roberta-base for register labeling, specifically fine-tuned for question-answer document identification
 
 This is the `xlm-roberta-base`, fine-tuned on register annotated data in English (https://github.com/TurkuNLP/CORE-corpus) and Finnish (https://github.com/TurkuNLP/FinCORE_full) as well as unpublished versions of Swedish and French (https://github.com/TurkuNLP/multilingual-register-labeling). The model is trained to predict whether a text includes something related to questions and answers or not.
 
-### Overview
-Language model: xlm-roberta-base
-
-Downstream-task: multi-class text classification
-
-
-### Usage
-
-the model can be used through a huggingface pipeline:
-```
-model = transformers.AutoModelForSequenceClassification.from_pretrained("TurkuNLP/xlmr-qa-register")
-tokenizer = transformers.AutoTokenizer.from_pretrained("xlm-roberta-base")
-pipe = transformers.pipeline(task="text-classification", model=model, tokenizer=tokenizer)
-```
 
 ### Hyperparameters
 ```