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catalog / Language & NLP / Argilla — Collaborative Data Annotation for LLMs
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Argilla — Collaborative Data Annotation for LLMs

Open-source annotation platform for building high-quality fine-tuning and RLHF datasets; integrates with Hugging Face Hub.

@ai-supply
Установки48k
Рейтинг★ 4.5
Отзывы16
↗ Исходный репозиторий

Argilla

Argilla is a collaboration platform for AI engineers and domain experts to annotate, curate, and quality-control datasets for fine-tuning and RLHF. It provides a polished web UI for labelling, a Python SDK for programmatic data management, and native Hugging Face Hub sync.

Key Features

  • Web UI: label text, images, ranking, rating, span, multi-label tasks
  • Custom schemas: define any labelling task with Argilla's dataset settings API
  • Human + model-in-the-loop: pre-label with your model, human reviews
  • RLHF/DPO: preference ranking and comparison tasks built-in
  • Hugging Face Hub: push/pull datasets directly with rg.Dataset.from_hub()
  • REST API + Python SDK + webhook integrations
  • Self-hostable via Docker; managed via Hugging Face Spaces

Quick Start

import argilla as rg

client = rg.Argilla(api_url="http://localhost:6900", api_key="argilla.apikey")

dataset = rg.Dataset(
    name="sentiment-annotation",
    settings=rg.Settings(
        fields=[rg.TextField(name="text")],
        questions=[rg.LabelQuestion(name="label", labels=["positive", "negative", "neutral"])],
    ),
)
dataset.create()

records = [rg.Record(fields={"text": "Argilla makes annotation easy!"})]
dataset.records.log(records)

Install via ai-supply

npx ai-supply add argilla-dataset-annotation-platform

Curated mirror of the open-source Argilla (Apache-2.0). Get it from the source.

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