import gradio as gr
from transformers import BertForSequenceClassification
from transformers import BertTokenizer
import torch

tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')
model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')

def predict(input_text):
    predictions = model(torch.tensor([tokenizer.encode(text)]))
    predictions=torch.nn.functional.softmax(predictions.logits,dim=-1)
    return input_text, {p["label"]: p["score"] for p in predictions} 

gradio_app = gr.Interface(
    fn=predict,
    inputs="text",
    outputs="text",
    title="我能做中文文本的情绪二分类",
)

if __name__ == "__main__":
    gradio_app.launch()