| |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
| from transformers_interpret import SequenceClassificationExplainer |
| model = AutoModelForSequenceClassification.from_pretrained("indobertweet-fine-tuned") |
| tokenizer = AutoTokenizer.from_pretrained("indolem/indobertweet-base-uncased") |
| classifier = pipeline('text-classification', model=model, tokenizer=tokenizer) |
|
|
| def classify(text): |
| text = text.strip().lower() |
| result = classifier(text) |
| yhat = result[0]['label'] |
| return result |
| |
| |
|
|
| import gradio as gr |
|
|
| iface = gr.Interface( |
| fn=classify, |
| inputs=[ |
| gr.Textbox(placeholder="Lewandowski bermain buruk sekali, Xavi benar-benar marah kepadanya", label="Enter text to classify emotions", lines=5) |
| ], |
| outputs=gr.Textbox(label="Classification Result"), |
| title="🔮 Emotion Classification", |
| description="Enter a text and classify its emotions." |
| ) |
| iface.launch() |