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import gradio as gr | |
import torch | |
from transformers import AutoModelForSequenceClassification,AutoTokenizer,pipeline | |
model = AutoModelForSequenceClassification.from_pretrained('SeyedAli/Persian-Text-Sentiment-Bert-V1') | |
tokenizer = AutoTokenizer.from_pretrained('SeyedAli/Persian-Text-Sentiment-Bert-V1',add_special_token=True) | |
def Sentiment(text): | |
pipline = pipeline(task="text-classification", model=model, tokenizer=tokenizer) | |
preds=pipline(text) | |
# return output | |
outputs = {} | |
for p in preds: | |
outputs[p["label"]] = p["score"] | |
return outputs | |
iface = gr.Interface(fn=Sentiment, inputs="text", outputs=gr.outputs.Label()) | |
iface.launch(share=False) |