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import gradio as gr
from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
from huggingface_hub import hf_hub_download
import numpy as np
tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
model = DistilBertForSequenceClassification.from_pretrained('jdmartinev/imdbreviews_classification_distilbert_v02')
id2label = {0: "negative", 1: "positive"}
def classify_text(input_text,id2label):
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model(**inputs)
pred = np.argmax(outputs)
return(pred)
demo = gr.Interface(classify_text, "text", "text")
demo.launch()
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