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app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
+
+# Load the model
+model_name = "tahirmuhammadcs/multi-ner-final"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForTokenClassification.from_pretrained(model_name)
+
+ner = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple")
+
+# Define prediction function
+def predict(text):
+    result = ner(text)
+    return result
+
+# Interface (you can hide this by setting `live=False`)
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(lines=4, placeholder="Enter text here..."),
+    outputs="json",
+    title="Multi-language NER",
+    description="Named Entity Recognition using Hugging Face Transformers."
+)
+
+# Launch the app
+demo.launch()

requirements.txt

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+transformers
+torch
+gradio