Name		Name	Last commit message	Last commit date
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static/css		static/css
templates		templates
.gitattributes		.gitattributes
LSTM_Attention3_10.h5		LSTM_Attention3_10.h5
LSTM_tokenizer.pickle		LSTM_tokenizer.pickle
Procfile		Procfile
README.md		README.md
TextGenertion_LSTM.ipynb		TextGenertion_LSTM.ipynb
app.py		app.py
requirements.txt		requirements.txt

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Text_Generation_model

Text Genareration Model is a Web Application that allows users to Generate NEWS related Sentences based to small sentence given as a input by the user.

This Model is based on LSTM with self-Attention Layer and trained on NEWS dataset

Effectiveness is very impressive it is able to generate sentence based of the given text but laking when it come to mainting the content as after some line generation like after generation of 3 lines it start to generate content which is not based to the the content But what it does at current stage is pretty good

[here](https://www.kaggle.com/datasets/rmisra/news-category-dataset)