ludwig 0.10.3

Declarative machine learning: End-to-end machine learning pipelines using data-driven configurations

08-16-2023 238 words 2 minutes 0 views

Contents

Declarative machine learning: End-to-end machine learning pipelines using data-driven configurations.

Stars: 10750, Watchers: 10750, Forks: 1162, Open Issues: 363

The ludwig-ai/ludwig repo was created 5 years ago and the last code push was 22 hours ago.
The project is extremely popular with a mindblowing 10750 github stars!

How to Install ludwig

You can install ludwig using pip

pip install ludwig

or add it to a project with poetry

poetry add ludwig

Package Details

Author: Piero Molino
License: Apache 2.0
Homepage: https://github.com/ludwig-ai/ludwig
PyPi:: https://pypi.org/project/ludwig/
GitHub Repo:: https://github.com/ludwig-ai/ludwig

No ludwig pypi packages just yet.

Errors

A list of common ludwig errors.

Code Examples

Here are some ludwig code examples and snippets.

GitHub Issues

The ludwig package has 363 open issues on GitHub

Update comment for predict to update Ludwig docs
[bug] Support preprocessing datetime.date date features
Add effective_batch_size to auto-adjust gradient accumulation
Lamma2 training on dataset downloaded from Huggingface.
Implement batch size tuning in for None type LLM trainer (used for batch inference)
[WIP] Enable strict schema enforcement
Bug in the Tutorial of Tabular Data Classification
ValueError: Unexpected keyword arguments: top_k
Re-enable Horovod installation and unit tests for torch nightly.
Missing documentation for Ludwig Explainer
[llm_text_generation] RuntimeError: Expected all tensors to be on the same device,
Image Classification: Config
Initial implementation of DaftDataFrameEngine
refactor: Remove dict support for initializer fields. (2/2)
Not uploading confusion_matrix (and others) figure to Comet ML

See more issues on GitHub

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