AI Examples

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The UFIT Research Computing AI Support Team maintains a suite of examples for computer vision and natural language processing tasks using the AI software stacks on HiPerGator. Users may copy these examples to their own space, add modifications, and follow the instructions to run these jobs on HiPerGator. Each example has a readme file with additional information in its directory.

Use https://support.rc.ufl.edu to submit ticket if you need help with the examples or have any AI questions.

Research Computing Github

We have examples available on the UF Research Computing Github.

Name Categories Description
Multinode Pytorch Launch distributed compute Launch a pytorch script for multiple GPUs on multiple nodes.
Py4AI Python education The episodes in this course are derived from work that is Copyrighted © by Software Carpentry. Additional information can be found at: http://software-carpentry.org/.
Understanding PyTorch Pytorch education Learn the Pytorch deep learning software by coding linear regression from the neural network perspective
Pytorch Convolutional Neural Network computer vision This training module is based off of the Deep Learning with Pytorch: A 60 minute blitz tutorial by Soumith Chintala. It has been updated and customized for running on HiPerGator


Catalog of available examples

Name Categories Location on HiPerGator Author Date added Description

Keras Tensorflow Quick CNN Computer vision /data/ai/examples/image/keras_tf_quickcnn Brian Stucky March 2021 This is an example of training a convolutional neural network for image recognition using Tensorflow.
Object Detection Tutorial Computer Vision /data/ai/examples/image/4.Object_Detection_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to generate a object detection on a video using pretrained models.
OpenCV Intro Tutorial Computer Vision /data/ai/examples/image/1.OpenCV_Intro_Tutorial Yunchao Yang Oct, 2022 This example illustrates the fundamentals of image processing techniques in opencv.
PyTorch Instance Segmentation Tutorial Computer Vision /data/ai/examples/image/5.PyTorch_Instance_Segmentation_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to train an instance segementation model using mask r-cnn model
PyTorch Transfer Learning Tutorial Computer Vision /data/ai/examples/image/3.PyTorch_Transfer_Learning_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to train a convolutional neural network for image classification using transfer learning.
TorchVision Intro Tutorial Computer Vision /data/ai/examples/image/2.TorchVision_Transforms_Tutorial Yunchao Yang Oct, 2022 This example illustrates the fundamentals of TorchVision in image transformation and augmentation
GraphCNN.ipynb Graphs /data/ai/examples/graphs Eric Stubbs August, 2021 A torch version of an article on Understanding Graph Convolutional Networks. The example shows how convolution learns from graphs even without training and backpropagation.
MONAI Medical Images Classification Tutorial Medical Image Processing /data/ai/examples/image/6.MONAI_Medical_Imaging_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to train an medical image classification model using MONAI
AI News Title Generation NLP /data/ai/examples/nlp/ai_title_generation Eric Stubbs May, 2022 See how a custom trained GPT model can enable knowledge exploration or brainstorming. A model is pretrained on a collection of AI news titles, then inferences help explore the data.
bertopic_topics.ipynb NLP /data/ai/examples/nlp Eric Stubbs May, 2021 Apply BERTopic software to examine topics of AI news articles.
embeddings-megatronbert345.ipynb NLP /data/ai/examples/nlp Eric Stubbs June, 2021 Create vector representations using Nvidia Megatron-BERT-345m.
embeddings-to-bertopics.ipynb NLP /data/ai/examples/nlp Eric Stubbs July 2021 Shows how to use vectors from a custom language model (Nvidia Megatron-BERT-345m) in BERTopic.
Example Multinode GPT Pretraining NLP /data/ai/examples/distributed-compute/pytorch_distributed_exampleGPT Eric Stubbs July, 2021 Use the pytorch distributed launch utility to pretrain a GPT language model using multiple nodes.
Improved Megatron GPT Text Generation NLP /data/ai/examples/nlp/megatronGPT_text_generation Eric Stubbs August, 2022 Megatron code was updated to allow for bulk prompt completion and language generation using a 23 billion parameter Megatron GPT language model trained by UFIT Research Computing.
inferences-megatronbert345.ipynb NLP /data/ai/examples/nlp Eric Stubbs July 2021 Demonstrates how to create a list of predictions for missing words in a sentence using Megatron-BERT-345m.
Language Model Inference Apps NLP /data/ai/examples/nlp/inference_apps Eric Stubbs May, 2022 Explore knowledge in Nvidia Megatron BERT and GPT models using notebooks by creating lists of the most likely predicted words.
MNLI Benchmark with UF Model NLP /data/ai/examples/nlp/multinli_benchmark Eric Stubbs August, 2022 Apply a 9 billion parameter Megatron BERT language model trained by UFIT Research Computing to an inference benchmark using improved code from Megatron. The model achieved a score of 87% after only 1 epoch of finetuning. State of the art score on NLI is 92%.
NeMo Text Classification NLP /data/ai/examples/nlp/nemotextclassify Eric Stubbs November, 2021 Train a language model to classify text with a set of labels. Requires labelled data.
Race Benchmark with UF Model NLP /data/ai/examples/nlp/race_benchmark_megatron Eric Stubbs August, 2022 Apply a 9 billion parameter Megatron BERT language model undertrained on only 400gb of data by UFIT Research Computing to a question answering benchmark using code from Nvidia Megatron-LM. The model achieved a score of 85% on middle school questions and 81% on high school questions after only 1 epoch on the QA training data. State of the art score on RACE is 92%.
summary-extractive.ipynb NLP /data/ai/examples/nlp Eric Stubbs May 2021 Use cosine similarity, a similarity matrix, and a centrality matrix to identify key sentences within an article that provide a summary of the main points.