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  ---
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  library_name: transformers
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  license: mit
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- language:
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  - tr
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  metrics:
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  - accuracy
 
 
 
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  pipeline_tag: text-classification
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  ---
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@@ -42,20 +45,22 @@ pip install torch
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  ## Example
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  ```python
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  from transformers import ConvBertTokenizer, ConvBertForSequenceClassification,TextClassificationPipeline
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- tokenizer = AutoTokenizer.from_pretrained("AIZinu/convBERT-turk-based-cyberbullying-tokenizer")
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- model = ConvBertForSequenceClassification.from_pretrained("convbert-classification")
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  pipe= TextClassificationPipeline(model=model, tokenizer=tokenizer)
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  print(pipe("Hadi modeli deneyelim"))
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  ```
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  ## Model Card Authors
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- * Bilge Nur BEKAR
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-
 
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  ---
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  library_name: transformers
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  license: mit
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+ language:
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  - tr
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  metrics:
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  - accuracy
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+ - f1
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+ - precision
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+ - recall
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  pipeline_tag: text-classification
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  ---
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  ## Example
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+
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  ```python
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  from transformers import ConvBertTokenizer, ConvBertForSequenceClassification,TextClassificationPipeline
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+ tokenizer = ConvBertTokenizer.from_pretrained("AIZinu/convBERT-turk-based-cyberbullying")
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+ model = ConvBertForSequenceClassification.from_pretrained("AIZinu/convBERT-turk-based-cyberbullying")
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  pipe= TextClassificationPipeline(model=model, tokenizer=tokenizer)
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  print(pipe("Hadi modeli deneyelim"))
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  ```
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+ Result:
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+ [{'label': 'LABEL_3', 'score': 0.9994651675224304}]
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  ## Model Card Authors
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+ * Bilge Nur BEKAR