README.md updated

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README.md

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----
-license: gpl-3.0
----
+## About the model
+It is a bert-based model created to determine the types of bullying that people use against each other in social media.
+Included classes;
+
+- Nötr
+- Kızdırma/Hakaret
+- Cinsiyetçilik
+- Irkçılık
+
+3388 tweets were used in the training of the model. Accordingly, the success rates in education are as follows;
+![alt text](/Users/seyma.sarigil/PycharmProjects/bert-base-turkish-bullying/src/image.jpg)
+
+
+## Example
+```sh
+from transformers import AutoTokenizer, TextClassificationPipeline, TFBertForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("nanelimon/bert-base-turkish-bullying")
+model = TFBertForSequenceClassification.from_pretrained("nanelimon/bert-base-turkish-bullying", from_pt=True)
+pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)
+
+print(pipe('Bu bir denemedir hadi sende dene!'))
+```
+Result;
+```sh
+[{'label': 'Nötr', 'score': 0.999175488948822}]
+```
+label= It shows which class the sent Turkish text belongs to according to the model.
+score= It shows the compliance rate of the Turkish text sent to the label found.
+
+## License
+
+gpl-3.0
+
+**Free Software, Hell Yeah!**