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Runtime error
| import gradio as gr | |
| from transformers import pipeline | |
| model_id = "GV05/distilbert-base-uncased-finetuned-emotion" | |
| classifier = pipeline("text-classification", model=model_id) | |
| label_to_emotion = { | |
| 'LABEL_0': 'sadness', | |
| 'LABEL_1': 'joy', | |
| 'LABEL_2': 'love', | |
| 'LABEL_3': 'anger', | |
| 'LABEL_4': 'fear', | |
| 'LABEL_5': 'surprise', | |
| } | |
| def classify_emotion(text): | |
| preds = classifier(text, return_all_scores=True) | |
| res = {} | |
| for x in preds[0]: | |
| res[label_to_emotion[x['label']]] = x['score'] | |
| return res | |
| image = gr.Textbox() | |
| label = gr.Label() | |
| examples = ["you are not too sensitive. you are not overreacting", | |
| "Thinking of you keeps me awake. Dreaming of you keeps me asleep. Being with you keeps me alive."] | |
| title = "Emotion Detector" | |
| description = "This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset" | |
| intf = gr.Interface(fn=classify_emotion, inputs=image, outputs=label, examples=examples, title=title, | |
| description=description) | |
| intf.launch(inline=False) | |