semantic-heb / app.py
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from transformers import AutoTokenizer, AutoModelForSequenceClassification ,pipeline
tokenizer = AutoTokenizer.from_pretrained("avichr/heBERT_sentiment_analysis")
model = AutoModelForSequenceClassification.from_pretrained("avichr/heBERT_sentiment_analysis")
sentiment_analysis = pipeline(
"sentiment-analysis",
model="avichr/heBERT_sentiment_analysis",
tokenizer="avichr/heBERT_sentiment_analysis",
return_all_scores = True
)
import gradio as gr
def sme(text):
return sentiment_analysis(text)
demo = gr.Interface(fn=sme, inputs="text", outputs="json")
demo.launch(share=True)