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metadata
title: ZenML Breast Cancer Classifier
emoji: 🦀
colorFrom: purple
colorTo: purple
sdk: gradio
sdk_version: 3.50.2
app_file: app.py
pinned: false
license: apache-2.0

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

📜 ZenML Stack Show Case

This project aims to demonstrate the power of stacks. The code in this project assumes that you have quite a few stacks registered already.

default

  • default Orchestrator
  • default Artifact Store
zenml stack set default
python run.py --training-pipeline

local-sagemaker-step-operator-stack

  • default Orchestrator
  • s3 Artifact Store
  • local Image Builder
  • aws Container Registry
  • Sagemaker Step Operator
zenml stack set local-sagemaker-step-operator-stack
zenml integration install aws -y
python run.py --training-pipeline

sagemaker-airflow-stack

  • Airflow Orchestrator
  • s3 Artifact Store
  • local Image Builder
  • aws Container Registry
  • Sagemaker Step Operator
zenml stack set sagemaker-airflow-stack
zenml integration install airflow -y
pip install apache-airflow-providers-docker apache-airflow~=2.5.0
zenml stack up
python run.py --training-pipeline

sagemaker-stack

  • Sagemaker Orchestrator
  • s3 Artifact Store
  • local Image Builder
  • aws Container Registry
  • Sagemaker Step Operator
zenml stack set sagemaker-stack
python run.py --training-pipeline