Examples¶
The following examples demonstrate how to use the Kubeflow SDK for distributed AI training and LLM fine-tuning.
PyTorch & HuggingFace Examples¶
Task |
Model |
Dataset |
Notebook |
|---|---|---|---|
Local Training |
CNN |
MNIST |
|
Image Classification |
CNN |
Fashion MNIST |
|
Question Answering |
DistilBERT |
SQuAD |
|
Speech Recognition |
Transformer |
Speech Commands |
|
Audio Classification |
CNN (M5) |
GTZAN |
DeepSpeed Examples¶
Task |
Model |
Dataset |
Notebook |
|---|---|---|---|
Text Summarization |
T5 |
CNN/DailyMail |
MLX Examples¶
Task |
Model |
Dataset |
Notebook |
|---|---|---|---|
Image Classification |
MLP |
MNIST |
|
LLM Fine-Tuning |
Llama 3.2-3B |
WikiSQL |
TorchTune Examples¶
Task |
Model |
Dataset |
Notebook |
|---|---|---|---|
LLM Fine-Tuning |
Llama 3.2-1B |
Alpaca |
Spark Examples¶
Task |
Example |
Description |
Code |
|---|---|---|---|
Basic Spark Client |
SparkClient API |
Basic |
|
Advanced Spark Configuration |
Driver / Executor Configuration |
Configure Spark jobs using Driver and Executor objects |
|
Connect to Existing Spark Cluster |
Existing Spark Connect Session |
Connect to an already running Spark Connect cluster |
|
URL-based Connection |
Spark Connect URL |
Connect to Spark Connect using a connection URL |