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UbiOps Technical Documentation

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How-To's & Tutorials
Troubleshooting
API Explorer
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Release Notes

UbiOps Technical Documentation

Documentation
Documentation
- Deployments
  Deployments
- Pipelines
  Pipelines
  - Operators
- Environments
  Environments
  - Installing OS-level packages
  - Environment Validation
- File storage
  File storage
- Training
- Making requests & processing data
  Making requests & processing data
- Compute & scaling settings
- Monitoring
  Monitoring
- Project & User Management
  Project & User Management
- Interfacing with UbiOps
  Interfacing with UbiOps
- Miscellaneous
  Miscellaneous
- Questions & Support
- Back to UbiOps.com
How-To's & Tutorials
How-To's & Tutorials
- Introduction
- How-to work with deployments
  How-to work with deployments
- How-to work with pipelines
  How-to work with pipelines
- How-to work with training
  How-to work with training
  - Training Checkpointing
  - Tracking training metrics on UbiOps
- How-to work with buckets & files
  How-to work with buckets & files
- How-to work with environments
  How-to work with environments
- How-to improve workflow
  How-to improve workflow
  - Set up CI/CD from Git
  - Add retry logic to your request function
- Starter Tutorials
  Starter Tutorials
  - UI Starter Tutorials
    
    UI Starter Tutorials
    
    UI deployment Starter Tutorial
    
    UI pipeline Starter Tutorial
    
    UI training Starter Tutorial
  - Client library Starter Tutorial
  - CLI Starter Tutorial
- Tutorials
  Tutorials
  - Model deployment
    Model deployment
    
    Deploying a Scikit-Learn model
    
    Deploying a TensorFlow model
    
    Deploying an XGBoost model
    
    Inference speed of ONNX vs TensorFlow
  - Model training
    Model training
    
    Training a Tensorflow model
    
    Tensorflow Checkpointing
    
    Retraining a PyTorch model
    
    Training an XGBoost model
  - Integration examples with cloud provider tools
    Integration examples with cloud provider tools
    
    Azure Data Factory & UbiOps
    
    Azure Machine Learning
    
    Azure Functions trigger
    
    Google Cloud Functions trigger
  - Integration examples with other tools
    Integration examples with other tools
    
    MLFlow Conversion
    
    Mendix integration
    
    GSheets RFM pipeline
    
    Streamlit integration
    
    Weights and Biases integration using FinBERT
    
    TensorRT integration
    
    NVIDIA RAPIDS Benchmark
  - GenAI (LLMs & CV)
    GenAI (LLMs & CV)
    
    Deploy Bert
    
    Deploy Stable Diffusion
    
    Deploy Llama 2
    
    Deploy Mistral 7B (development set-up)
    
    Fine-tuning Falcon 1B
    
    Mistral RAG
  - Working with pipelines
    Working with pipelines
    
    Pokemon Pipeline
    
    Creating a pipeline with R and Python deployments
  - R Tutorials
    R Tutorials
    
    Deploying an R XGboost model
    
    Deploying an R XGboost pipeline
    
    Creating a pipeline with R and Python deployments
  - UI tutorials
    UI tutorials
    
    Multiplying a number
    
    Load & run a pre-trained model
    
    Image recognition
    
    GPU deployment
    
    Customer segmentation
Troubleshooting
Troubleshooting
- Problems with building
  Problems with building
- Problems during requests
  Problems during requests
API Explorer
CLI
CLI
- Installation Guide
- Get Started
- Documentation
  Documentation
Client Libraries
Client Libraries
- Python
  Python
- R
  R
  - Installation Guide
  - Getting Started
  - Documentation
    Documentation
    
    Blobs
    
    Deployment Requests
    
    Deployments
    
    Environments
    
    Files
    
    Imports And Exports
    
    Metrics
    
    Monitoring
    
    Organizations
    
    Pipeline Requests
    
    Pipelines
    
    Projects
    
    Request Schedules
    
    Roles
    
    Service Users
    
    Status
    
    User
    
    Webhooks
Release Notes
Release Notes

Table of contents

Properties

TemplateDeploymentList¶

Properties¶

Name	Type	Notes
id	str	[optional] [readonly]
details	str or dict(str, str)	[optional]