text_classification/app.py

29 lines
1007 B
Python

import gradio as gr
from transformers import pipeline
def inference(sequence_to_classify):
model_path="mDeBERTa-v3-base-mnli-xnli"
classifier = pipeline("zero-shot-classification", model=model_path)
candidate_labels = ["politics", "economy", "entertainment", "environment"]
output = classifier(sequence_to_classify, candidate_labels, multi_label=False)
return output
examples=[["Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU"]]
with gr.Blocks() as demo:
gr.Markdown(
"""
# Text classification:mDeBERTa-v3-base-mnli-xnli
这是mDeBERTa-v3-base-mnli-xnli的Gradio Demo。输入你想要的英文文本或者点击下面的示例文本来加载它。
""")
with gr.Row():
text_input = gr.Textbox()
text_output = gr.Textbox()
image_button = gr.Button("上传")
image_button.click(inference, inputs=text_input, outputs=text_output)
gr.Examples(examples,inputs=text_input)
demo.launch(server_name="0.0.0.0")