ValidMind Library
Project description
ValidMind Library
ValidMind’s Python Library contains a suite of developer tools and methods designed to automate the documentation and validation of your models.
The Library is designed to be model agnostic. If your model is built in Python, ValidMind's Python library will provide all the standard functionality without requiring your developers to rewrite any functions.
The Library provides a rich suite of documentation tools and test suites, from documenting descriptions of your dataset to testing your models for weak spots and overfit areas. The Developer Framework helps you automate the generation of model documentation by feeding the ValidMind platform with documentation artifacts and test results to the ValidMind platform.
Installation
To install the ValidMind Library and all optional dependencies, run:
pip install validmind[all]
To install the Library without optional dependencies (core functionality only), run:
pip install validmind
Extra dependencies
The Library has optional dependencies that can be installed separately to support additional model types and tests.
-
LLM Support: To be able to run tests for Large Language Models (LLMs), install the
llm
extra:pip install validmind[llm]
-
PyTorch Models: To use pytorch models with the Library, install the
torch
extra:pip install validmind[torch]
-
Hugging Face Transformers: To use Hugging Face Transformers models with the Library, install the
transformers
extra:pip install validmind[transformers]
-
R Models: To use R models with the Library, install the
r
extra:pip install validmind[r-support]
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