Instructions to use madha98/Text_Generation_RNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use madha98/Text_Generation_RNN with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://madha98/Text_Generation_RNN") - Notebooks
- Google Colab
- Kaggle
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license: mit
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license: mit
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# Automatic Text Generation Using SimpleRNN
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## Overview
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It contains code and resources for Automatic Text Generation. The goal is to explore and implement state-of-the-art methods in natural language processing (NLP) to generate coherent and contextually relevant text.
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## Introduction
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Text generation is a fascinating field within natural language processing that involves creating textual content using machine learning models. This project aims to showcase different techniques and libraries for automatic text generation, providing a starting point for enthusiasts and practitioners interested in this area.
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## License
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This project is licensed under the MIT License
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### Happy CODING...!! 💻
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