Generative Artificial Intelligence and Large Langage Model using Python
Under Development!
This tutorial is not in its final state. The content may change a lot in the next months. Because of this status, it is also not listed in the topic pages.
| Author(s) |
Raphael Mourad
|
OverviewQuestions:
Objectives:
to do
Requirements:
pretraining LLM for DNA
finetuning LLM
zeroshot prediction for DNA variants and synthetic DNA sequence generation.
- Introduction to Galaxy Analyses
- tutorial Hands-on: Introduction to Python
- tutorial Hands-on: Python - Warm-up for statistics and machine learning
- slides Slides: Foundational Aspects of Machine Learning using Python
- tutorial Hands-on: Foundational Aspects of Machine Learning using Python
- slides Slides: Neural networks using Python
- tutorial Hands-on: Neural networks using Python
- slides Slides: Deep Learning (without Generative Artificial Intelligence) using Python
- tutorial Hands-on: Deep Learning (without Generative Artificial Intelligence) using Python
Time estimation: 3 hoursLevel: Intermediate IntermediateSupporting Materials:Published: Mar 11, 2025Last modification: Mar 11, 2025License: Tutorial Content is licensed under Creative Commons Attribution 4.0 International License. The GTN Framework is licensed under MITversion Revision: 1
Best viewed in a Jupyter NotebookThis tutorial is best viewed in a Jupyter notebook! You can load this notebook one of the following ways
Run on the GTN with JupyterLite (in-browser computations)
Launching the notebook in Jupyter in Galaxy
- Instructions to Launch JupyterLab
- Open a Terminal in JupyterLab with File -> New -> Terminal
- Run
wget https://training.galaxyproject.org/training-material/topics/statistics/tutorials/gai-llm-with-python/statistics-gai-llm-with-python.ipynb- Select the notebook that appears in the list of files on the left.
Downloading the notebook
- Right click one of these links: Jupyter Notebook (With Solutions), Jupyter Notebook (Without Solutions)
- Save Link As..