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Create app.py
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app.py
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from transformers import pipeline
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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id2label = { 0: "sadness", 1:"joy", 2:"love", 3:"anger", 4:"fear", 5:"surprise" }
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label2id = { "sadness":0, "joy":1, "love":2, "anger":3, "fear":4, "surprise":5}
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tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
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model = AutoModelForSequenceClassification.from_pretrained("Sadiksha/sentiment_analysis_bert", id2label=id2label, label2id=label2id)
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pipe = pipeline('sentiment-analysis', model = model, tokenizer=tokenizer)
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import gradio as gr
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def predict(text):
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return pipe(text)[0]['label']
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iface = gr.Interface(
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fn=predict,
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inputs='text',
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outputs='text',
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examples=[["I just received an unexpected gift from my friend and it made my day!"],
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["I am feeling so lonely without my family around during the holidays."],
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["I have a fear of spiders, they give me the creeps."]]
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)
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iface.launch()
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