| import gradio as gr | |
| from transformers import pipeline | |
| model = pipeline("text-classification", model="mdeniz1/turkish-sentiment-analysis-bert-base-turkish-uncased") | |
| def predict(prompt): | |
| sentiment=model(prompt) | |
| if sentiment[0]['label']=='LABEL_2': | |
| return 'positive' | |
| elif sentiment[0]['label']=='LABEL_1': | |
| return 'neutral' | |
| else: | |
| return 'negative' | |
| title = "Turkish Sentiment Analysis" | |
| description = """ | |
| The bot has been trained to analyze the sentiment of Turkish text. When provided with a Turkish prompt, it can determine whether the text expresses a neutral, negative, or positive sentiment. | |
| """ | |
| textbox = gr.Textbox(label="Enter a text here:", lines=1) | |
| gr.Interface( | |
| fn=predict, | |
| inputs=textbox, | |
| outputs="text", | |
| title=title, | |
| description=description, | |
| examples=[["ortam oldukça güzel"], ["senden bir cacık olmaz"]], | |
| ).launch() |