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SPECIFICTION
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Argilla vs LabelU

Argilla

argilla.io

LabelU

opendatalab.github.io

Side by side

FigureArgillaLabelU
Price fromFree—
Free planYes—
Free trial——
Open source——
WebYesYes
Windows—Yes
macOS—Yes
LinuxYes—
APIYes—
Self-hostedYesYes
Plans published10
Spec score · Data Labeling Software8.2 (#8)7.2 (#21)
DeploymentArgilla can be deployed on Hugging Face Spaces or on a local machine or server using Docker Compose.LabelU can be installed locally with pip and run at localhost:8000; the README specifies Python 3.11.
PurposeArgilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets.LabelU is a multimodal data annotation platform for image, video, and audio tasks.

Plans

Argilla

  • ArgillaFree

Argilla pricing →

LabelU

No plans published.

LabelU pricing →

In their own words

Argilla

Argilla is a free collaboration tool for AI engineers and domain experts building datasets with human feedback. It supports NLP, LLM, and multimodal projects, including classification, named entity recognition, retrieval-augmented generation, and preference tuning. Contributors can provide labels, ratings, rankings, and written responses; annotation tools include filters, AI feedback suggestions, and semantic search. The system handles text and images, while custom fields can represent audio, video, or other content rendered as base64 or HTML. It is compatible with Hugging Face and spaCy, and tutorials cover SetFit and LlamaIndex. Deployment options include Hugging Face Spaces or a local machine or server using Docker Compose. A Python SDK connects to an Argilla server with an API URL and key, and the server exposes REST API documentation. Datasets and records can be moved to or from Python, local disk, and the Hugging Face Hub. Argilla supports OAuth2 through Hugging Face, GitHub, and Google by default. It does not train models; on Hugging Face Spaces, data on ephemeral free storage is lost when the Space restarts.

Visit argilla.io

LabelU

LabelU has no write-up on Specifiction yet; its figures are above.

Visit opendatalab.github.io