Update README.md

README.md

@@ -11,4 +11,45 @@ license: mit
 short_description: To predict next number by sequence
 ---
 
+# 🔢 Next Number Predictor using LSTM
+
+This is a simple Gradio web app that uses a trained LSTM model to predict the **next number** in a sequence.
+
+---
+
+## 🚀 Features
+
+- Predicts the next number given a fixed-length numeric sequence.
+- Clean and interactive Gradio interface.
+- Easy to run locally or deploy to platforms like Hugging Face Spaces.
+
+---
+
+## 📁 Files Included
+
+- `main.py` – The Gradio web app script.
+- `requirements.txt` – Python dependencies.
+- `next_number_model.h5` – Your trained LSTM model (not included in this repo – you must provide your own).
+
+---
+
+## 📥 Example Input
+
+If your model was trained with a **window size of 3**, enter:
+
+example code:
+
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.layers import LSTM, Dense
+
+model = Sequential([
+    LSTM(50, activation='relu', input_shape=(3, 1)),
+    Dense(1)
+])
+
+model.compile(optimizer='adam', loss='mse')
+model.fit(X_train, y_train, epochs=200, verbose=1)
+model.save("next_number_model.h5")
+
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference