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fondant

ml6team/fondant

Production-ready data processing made easy and shareable

GraphCanon updated 4w · GitHub synced 4w

358 stars29 forksLast push 6mo Python Apache-2.0

Decision brief

Fondant is designed for Python users needing to create efficient data pipelines for processing, fine-tuning ML models, sharing these workflows.

Good fit when

  • When you require a tool that simplifies the creation of machine-learning data pipelines and supports community sharing.
  • Suitable if your workflow includes fine-tuning existing large foundation models.

Avoid when

  • Avoid using Fondant if you prefer tools without Python-centric integration or seek non-sharing-friendly development environments.
  • Not recommended for workflows that do not involve machine learning data processing or large model training.

Observed Jul 15, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Slowing (154d since push)
As of 4w
Provenance
Not a fork · Organization account
As of 4w
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install fondant
PyPI

Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A Python-based tool for creating pipelines to process data efficiently, designed with sharing in mind, facilitating workflows involving fine-tuning and foundation models.

Capability facts

CLI
CLI entrypoint

Source: pyproject.toml:[project.scripts] · Jul 25, 2026

Languages
python

Source: github.language+pyproject.toml · Jul 25, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 25, 2026)

pip install fondant
Source link

Tags

README

💨 Getting Started

Fondant allows you to easily define workflows comprised of both reusable and custom components. The following example uses the reusable load_from_hf_hub component to load a dataset from the Hugging Face Hub and process it using a custom component that will resize the images resulting in a new dataset.

import pyarrow as pa

from fondant.dataset import Dataset

---

## ⚒️ Installation

First, run the basic Fondant installation:

pip install fondant


Fondant also includes extra dependencies for specific runners, storage integrations and publishing 
components to registries. The dependencies for the local runner (docker) is included by default.

For more detailed installation options, check the [**installation page**](https://fondant.ai/en/latest/guides/installation/)on our documentation.

For agents

This page has a .md twin and JSON over the API.

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