Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.
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Updated
Aug 9, 2019 - Jupyter Notebook
Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.
Text Generation notebook using TensorFlow 2.0
Notebook for running GPT-J/GPT-J-6B – the cost-effective alternative to ChatGPT, GPT-3 & GPT-4 for many NLP tasks. Available on IPUs as a Paperspace notebook.
Compilation of notebooks.
A tutorial on GPT2 language model training with texts from Shakespeare
the notebook and generated texts created for the DAGPap22
A jupyter notebook to generate song lyrics using LSTM network.
Generates ballads using Deep learning . Using LSTMs and data of some famous ballads . Generates new ballads and autocompletes with initial given texts .
Generative AI workshop delivered at PyDataBCN 2023
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Repo to store code for #66DaysOfData challenge by Ken Jee. Includes notebooks and code for different concepts and technologies in data science for learning purposes.
In this notebook, I'll construct a character-level LSTM with PyTorch. The network will train character by character on some text, then generate new text character by character. As an example, I will train on Anna Karenina. This model will be able to generate new text based on the text from the book!
Text generation using a character-based RNN with LSTM cells. We will work with a dataset of Shakespeare's writing from Andrej Karpathy's The Unreasonable Effectiveness of Recurrent Neural Networks. Given a sequence of characters from this data ("Shakespear"), train a model to predict the next character in the sequence ("e"). Longer sequences of …
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