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1
Introduction
2
What is SageMaker
3
Getting started
4
Preprocessing
5
S3 Integration
6
Hiking Phase Hub
7
Starting the Training
8
Accessing the Model
9
How SageMaker Works
10
Using Existing Training Scripts
11
Leveraging the Trainer from Transformers
12
Hyperparameter Search with SageMaker
13
What does a day in the life of Philip look like
14
Where do you see the most exciting developments in this space
15
What are the sort of challenges that happen when you want to make these models smaller
16
What is Optimum
17
GPU Instances
Description:
Explore managed training with Amazon SageMaker and Hugging Face Transformers in this 25-minute video featuring Philipp Schmid, Machine Learning Engineer and Tech Lead at Hugging Face. Learn about SageMaker integration, preprocessing, S3 integration, and the Hugging Face Hub. Discover how to start training, access models, and leverage existing training scripts and the Transformer Trainer. Gain insights into hyperparameter search, GPU instances, and the challenges of model optimization. Hear Philipp's perspective on exciting developments in the field and learn about Optimum, a tool for model optimization. Get a glimpse into a day in the life of a Machine Learning Engineer and the future of NLP model democratization and productionization.

Managed Training with Amazon SageMaker and Transformers

HuggingFace
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