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title: README
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sdk: static
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<p align="center">
<img src="https://raw.githubusercontent.com/ml6team/fondant/main/docs/art/fondant_banner.svg" height="250px"/>
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<p align="center">
<i>Sweet data-centric foundation model fine-tuning</i>
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<a href="https://fondant.readthedocs.io/en/stable/"><strong>Explore the docs »</strong></a>
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<a href="https://discord.gg/HnTdWhydGp"><img alt="Discord" src="https://dcbadge.vercel.app/api/server/HnTdWhydGp?style=flat-square"></a>
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**Fondant helps you create high quality datasets to train or fine-tune foundation models such as:**
- 🎨 Stable Diffusion
- 📄 GPT-like Large Language Models (LLMs)
- 🔎 CLIP
- ✂️ Segment Anything (SAM)
- ➕ And many more
## 🪤 Why Fondant?
Foundation models simplify inference by solving multiple tasks across modalities with a simple
prompt-based interface. But what they've gained in the front, they've lost in the back.
**These models require enormous amounts of data, moving complexity towards data preparation**, and
leaving few parties able to train their own models.
We believe that **innovation is a group effort**, requiring collaboration. While the community has
been building and sharing models, everyone is still building their data preparation from scratch.
**Fondant is the platform where we meet to build and share data preparation workflows.**
Fondant offers a framework to build **composable data preparation pipelines, with reusable
components, optimized to handle massive datasets**. Stop building from scratch, and start
reusing components to:
- Extend your data with public datasets
- Generate new modalities using captioning, segmentation, translation, image generation, ...
- Distill knowledge from existing foundation models
- Filter out low quality data
- Deduplicate data
And create high quality datasets to fine-tune your own foundation models.
<p align="right">(<a href="#chocolate_bar-fondant">back to top</a>)</p>
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