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Emmi AI Core documentation

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Tutorials

Prerequisites
Getting Started: Install & Verify
Training First Model (with Configs)
Training First Model (with Code)
Running First Inference

How-to Guides

Working with the CLI
How to Load a Custom Dataset
How to Use Private Data Source
How to Write Your Own Data Preprocessors
How to Write Your Own Data Collators
How to Configure All Training Options
How to Use Custom Model
How to Write Custom Loss or Metrics
How to Run Inference via the CLI
How to Run Inference via the Code

Explanation

Overview
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Disk Caching

Reference

Emmi Data Management
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- emmi_data_management
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  - emmi_data_management.checkpoint
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    - emmi_data_management.checkpoint.resolver
    - emmi_data_management.checkpoint.types
  - emmi_data_management.cli
  - emmi_data_management.cli_aws
  - emmi_data_management.cli_checkpoint
  - emmi_data_management.cli_huggingface
  - emmi_data_management.cli_utils
  - emmi_data_management.cli_verification
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  - emmi_data_management.logging_config
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Emmi Inference Module
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- emmi_inference
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  - emmi_inference.api
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  - emmi_inference.cli_utils
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  - emmi_inference.common
  - emmi_inference.dataset_registry
  - emmi_inference.datasets
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    - emmi_inference.datasets.shapenet
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High level API (emmi)
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- emmi
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        emmi.modules.preprocessors.normalizers.mean_std_normalization
        
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Low level API (ksuit)
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        ksuit.data.wrappers.dataset_wrappers.repeat_wrapper
        
        ksuit.data.wrappers.dataset_wrappers.shuffle_wrapper
        
        ksuit.data.wrappers.dataset_wrappers.subset_wrapper
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emmi_inference.examples.run_upt¶

Functions¶

Module Contents¶

emmi_inference.examples.run_upt.run_upt()¶

Return type:: None

emmi_inference.logging_config

emmi_inference.examples.run_transolver

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emmi_inference.examples.run_upt
- Functions
- Module Contents
  - run_upt()