metadata

title: Next Number Predictor
emoji: 😻
colorFrom: blue
colorTo: gray
sdk: gradio
sdk_version: 5.38.0
app_file: app.py
pinned: false
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:3,4,5

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