| import gradio as gr | |
| from transformers import pipeline | |
| def generate_story(story): | |
| ner = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions") | |
| return str(ner(story)) | |
| demo = gr.Interface ( | |
| fn=generate_story, | |
| description="Sentiment analysis multi-class with (SamLowe/roberta-base-go_emotions", | |
| examples=[ | |
| ["I am looking forward to a good maths session."], | |
| ["Good that they broke up, not like it was going anywhere anyways."], | |
| ["I am going to punch through his face next time he mentions notes!"] | |
| ], | |
| inputs=[gr.Textbox(lines=7, label="Text")], | |
| outputs=[gr.Textbox(lines=7, label="Multiclass Sentiment Analysis")] | |
| ) | |
| demo.launch(share=True) |