Add application files

app.py

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+import gradio as gr
+import numpy
+from scipy.special import softmax
+
+from transformers import (
+    AutoTokenizer,
+    AutoConfig,
+    AutoModelForSequenceClassification
+)
+
+model_path = "EmotiScan/amazon-comments-bert"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+
+def get_sentiments(text):
+
+    encoded_input = tokenizer(text, return_tensors='pt')
+    output = model(**encoded_input)
+
+    scores = output[0][0].detach().numpy()
+    scores = softmax(scores)
+
+    labels = ['Terrible', 'Bad', 'Good', 'Very Good', 'Excellent']
+    scores = {l:float(s) for (l,s) in zip(labels, scores) }
+
+    return scores
+
+try_out = gr.Interface(
+    fn=get_sentiments,
+    inputs=gr.Textbox(placeholder="Input the product review"),
+    outputs=gr.Textbox(),
+    # interpretation="default",
+    css= "body {background-color: black}"
+)
+
+try_out.launch()
+

requirements.txt

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+transformers
+torch
+scipy
+gradio