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import gradio as gr |
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from fastai.text.all import * |
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from fastai.text.all import * |
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from datasets import load_dataset |
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from spacy.lemmatizer import Lemmatizer |
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learn = load_learner('export.pkl') |
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labels = ['anger','joy','optimism','sadness'] |
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def predict(text): |
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aux1,aux2,probs = learn.predict(text) |
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return {labels[i]: float(probs[i]) for i in range(len(labels))} |
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gr.Interface(fn=predict, inputs=gr.inputs.Textbox(lines=3,placeholder="Type a phrase that has some emotion",label="Input Text",), outputs=gr.outputs.Label(num_top_classes=4),examples=[ |
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'No but thats so cute. Atsu was probably shy about photos before but cherry helped her out uwu ', |
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]).launch(share=False) |
