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LSTM-based Language Model for Next Token Prediction
Overview
This project implements an LSTM-based language model that predicts the next token in a sequence. It has been trained on English text data and is capable of generating coherent text based on given seed input.
Features
- LSTM architecture for effective sequential learning.
- Ability to generate text based on a seed phrase.
- Training and validation loss monitoring during training.
- Saving and loading of model checkpoints.
Installation
To run this project, ensure you have the following libraries installed:
pip install torch torchvision matplotlib pandas huggingface_hub
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