https://dvc.org/

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    DataChain

    Wrangle unstructured data in Python using AI helpers at scale

     

    DVC Studio

    Track experiments and share insights from ML projects

     

    VS Code Extension

    Local ML model development and experiment tracking

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 by Iterative

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      + Datachain logoDataChain
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Get startedGet Enterprise
What's new

Scalable PDF Document Processing with DataChain and Unstructured.io

 
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[M][unstructur]

Extract and parse text from documents and create vector embeddings in
a scalable and distributed way (and less than 70 lines of code). Read
more.

DataChain Open-Source Release
A New Way to Manage your Unstructured Data
Star us on GitHub

Data Version Control
- and much more -
for the GenAI era

Free and open source, forever.

Manage and version images, audio, video, and text files in storage
and organize your ML modeling process into a reproducible workflow.

DVC Logo

GenAI DataChain

 
---Github Logo
DVC Logo

Data and model versioning

 
13.6KGithub Logo
[svg]
VisualizationVisualization
Explore and enrich annotated datasets with custom embeddings,
auto-labeling, and bias removal at billion-file scale -- without
modifying your data.
Connect to versioned data sources and code with pipelines, track
experiments, register models -- all based on GitOps principles.
Learn about DataChain
Download DVC

Get Started with

Datachain Logo

  * Filter a billion samples in seconds
   
    Datasets are getting larger, but the ability to iterate rapidly
    and efficiently is as important as ever.
   
  * Create datasets from queries
   
    Save the results of a query in a dataset that you can use to
    train your ML models.
   
Star us on Github

DataChain and DVC: Better Together

Build the datasets you need without modifying your data sources.
Create pipelines that connect your versioned datasets, code, and
models together for effective experiment tracking the GitOps way.

Get Started with

DVC Logo

  * Connect storage to repo
   
    Keep large data and model files alongside code and share via your
    cloud storage.
   
  * Configure steps as you go
   
    Declare dependencies and outputs at each step to build
    reproducible end-to-end pipelines.
   
  * Track experiments in Git
   
    Track experiments in your repo, compare results and restore
    entire experiment states cross-team.
   
Get started
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pip, conda, brew
macOSWindowsLinux DebLinux RPM
Get VS Code ExtensionDVC For VS CodeGet VS Code Extension

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