Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

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.

Text Generation notebook using TensorFlow 2.0

Compilation of notebooks.

This repository contains HTML versions of various Jupyter notebooks. These files are accessible directly in a web browser, allowing for easy viewing and sharing of notebook content without requiring a Jupyter Notebook environment.

This repository provides Jupyter notebooks to interact with Mistral Large Language Models (LLMs) for tasks including chatbot development, retrieval-augmented generation, and text generation. These notebooks are designed to help users leverage Mistral models in a range of applications, from conversational AI to content generation.

This repository contains Jupyter notebooks for working with Anthropic Large Language Models (LLMs), providing tools to explore chat-based interactions, retrieval-augmented generation, and text generation. These notebooks serve as a practical introduction to leveraging Anthropic models for various applications.

This repository contains Jupyter notebooks to explore and utilize OpenAI's Large Language Models (LLMs) for various applications, including chatbots, retrieval-augmented generation, text generation, prompt engineering, and vector embedding. These notebooks provide a comprehensive toolkit for working with OpenAI models in diverse contexts.

the notebook and generated texts created for the DAGPap22

A jupyter notebook to generate song lyrics using LSTM network.

A tutorial on GPT2 language model training with texts from Shakespeare

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"

Hands‑on experiments with neural sequence models. To generate text and tackle translation. Each colab notebook go through data prep, model building, training loops and evaluation.

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.

Sales Script AI is a tool that generates tailored sales scripts using AI-driven natural language processing techniques in an interactive Jupyter Notebook environment.

The LLM FineTuning and Evaluation project 🚀 enhances FLAN-T5 models for tasks like summarizing Spanish news articles 🇪🇸📰. It features detailed notebooks 📚 on fine-tuning and evaluating models to optimize performance for specific applications. 🔍✨

Natural language processing (NLP) tasks: text classification and text generation. The notebooks explore different techniques and models for handling these tasks, offering insights into common challenges and solutions.

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!