Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""NER_APP
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/#fileId=https%3A//storage.googleapis.com/kaggle-colab-exported-notebooks/ner-app-4d7a2843-05be-4536-8268-25e14a665793.ipynb%3FX-Goog-Algorithm%3DGOOG4-RSA-SHA256%26X-Goog-Credential%3Dgcp-kaggle-com%2540kaggle-161607.iam.gserviceaccount.com/20250116/auto/storage/goog4_request%26X-Goog-Date%3D20250116T193935Z%26X-Goog-Expires%3D259200%26X-Goog-SignedHeaders%3Dhost%26X-Goog-Signature%3Da8514916063f2f41f6c07de8e2e3ff8b6a302fff2401fd4e3f97cc8e31eaa05faa728975260701754e4f739c8a30815b7c041548193448195812b23254b93d8e654e7a4b34a3a83437a6a9ef7fbc704caba614cac7098b39e0b4165f64960cadf1c413af998265888cc5bb89263cc34ab7580decc1c802c88c8b0e6364a1d7aa79952445153f5094b8a2a9578fc4a493ffcdbcce10f057fccdc5c1b39518ee4b9cd832835bdd8e2b256d515615344ea3d6b0bbbf52212f6dd46780fba5145cbd7d496cca18c9ae6d46c43b2b908dc33d2182a401232ff258c65d63c37bbded8182fcdfd17ee795f4132b026a15664a48f9bb668561007e2a9ff9fbd8243e5a38
+"""
+
+# This Python 3 environment comes with many helpful analytics libraries installed
+# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
+# For example, here's several helpful packages to load
+
+import numpy as np # linear algebra
+import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
+
+# Input data files are available in the read-only "../input/" directory
+# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory
+
+import os
+for dirname, _, filenames in os.walk('/kaggle/input'):
+    for filename in filenames:
+        print(os.path.join(dirname, filename))
+
+# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All"
+# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session
+
+!pip install -q transformers
+
+from transformers import pipeline
+
+ner_pipeline = pipeline("ner", model="Tirendaz/roberta-base-NER")
+
+text = "I am Tim and I work at Google"
+
+ner_pipeline(text)
+
+text_tr = "Benim adım Ali ve Trendyol'da çalışıyorum"
+ner_pipeline(text_tr)
+
+ner_pipeline(text_tr, aggregation_strategy = "simple")
+
+def ner(text):
+  output = ner_pipeline(text, aggregation_strategy="simple")
+  return {"text": text, "entities": output}
+
+!pip install -q gradio
+
+import gradio as gr
+
+examples = [
+    "My name is Tim and I live in California",
+    "Ich arbeite bei Google in Berlin",
+    "Ali, Ankara'lı mı?"
+]
+
+demo = gr.Interface(
+    ner,
+    gr.Textbox(placeholder="Enter sentence here..."),
+    gr.HighlightedText(),
+    examples=examples
+)
+
+demo.launch(share=True)
+