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---
language: en
license: mit
tags:
- keras
- lstm
- spam-detection
- binary-classification
- text-classification
- email
library_name: keras
model_name: LSTM Spam Detector
pipeline_tag: text-classification
---
# 🧠LSTM Spam Detector
This repository contains a simple LSTM-based binary text classification model to detect **spam messages**, built using **Keras** and trained on a small dataset of English spam and non-spam messages.
---
## 🚀 How to Use
You can use the model and tokenizer in your own code like this:
```python
from tensorflow.keras.models import load_model
from huggingface_hub import hf_hub_download
import pickle
# Download files from Hugging Face Hub
model_path = hf_hub_download("lokas/lstm-spam-detector", "model.h5")
tokenizer_path = hf_hub_download("lokas/lstm-spam-detector", "tokenizer.pkl")
# Load model and tokenizer
model = load_model(model_path)
with open(tokenizer_path, "rb") as f:
tokenizer = pickle.load(f)
# Predict a sample message
from tensorflow.keras.preprocessing.sequence import pad_sequences
def predict_spam(text):
seq = tokenizer.texts_to_sequences([text])
padded = pad_sequences(seq, maxlen=10)
pred = model.predict(padded)[0][0]
return "🚫 Spam" if pred > 0.5 else "✅ Not Spam"
print(predict_spam("Win a free iPhone now!"))
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