inital

mDeBERTa_v3_base_mnli_xnli/app.py

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+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
+    Gradio Demo for mDeBERTa-v3-base-mnli-xnli. To use it, simply type in text, or click one of the examples to load them.
+    """)
+    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()

mDeBERTa_v3_base_mnli_xnli/mDeBERTa-v3-base-mnli-xnli

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+Subproject commit 9086d78af18a62546cf05a768934d291684d6309