Upload 3 files

app.py

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+import streamlit as st
+import numpy as np
+from sklearn.feature_extraction import CountVectorizer
+from tensorflow.keras.models import load_model
+
+model=load_model("model.h5")
+def transform(password):
+    character=[]
+    for i in password:
+        character.append(i)
+    return character
+vect=CountVectorizer(tokenizer=transform)
+input=st.text_input("Your Password",type="password")
+data=vect.fit_transform(input)
+if st.button("Predict"):
+    prediction=model.predict(data)
+    class_names=["Weak","Medium","Strong"]
+    prediction=class_names(np.argmax(prediction))
+    st.write(prediction)

model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:653e6066760ee1ddee2036a034a06c8d876b35b132a52eb6810a3b2e9e3f84da
+size 463360

requirements.txt

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+scikit-learn
+numpy
+streamlit
+tensorflow