🧠
distilabel model by Argilla Io
⭐ 48.5
🧠
Model

distilabel

by Argilla Io argilla-io/distilabel
Free2AITools Nexus Index
48.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 59
P: Popularity 62
R: Recency 99
Q: Quality 70
Tech Context
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 48.5 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID argilla-io/distilabel
License Apache-2.0
Provider github
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{gh_tool_argilla_io_distilabel,
  author = {Argilla Io},
  title = {distilabel Model},
  year = {2026},
  howpublished = {\url{https://github.com/argilla-io/distilabel}},
  note = {Accessed via Free2AITools.}
}
APA Style
Argilla Io. (2026). distilabel [Model]. Free2AITools. https://github.com/argilla-io/distilabel

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ Git Clone
git clone https://github.com/argilla-io/distilabel

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 59
Popularity (P) 62
Recency (R) 99
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for distilabel: Authority (A:59), Popularity (P:62), Recency (R:99), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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πŸš€ What's Next?

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Deployment reference

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Technical Deep Dive

[!IMPORTANT]
The original authors have moved on to other projects. A group of community members have recently joined the GitHub project as collaborators to maintain the project and are actively working towards the next release. Check out the develop branch for access to the latest fixes and improvements in the meantime.

Distilabel Logo

Synthesize data for AI and add feedback on the fly!

CI CI

Distilabel is the framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.

If you just want to get started, we recommend you check the documentation. Curious, and want to know more? Keep reading!

Why use dis

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

GitHub Repository
3.3KStars
246Forks
Repo Issues
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-tool--argilla-io--distilabel
slug
argilla-io--distilabel
source
github
author
Argilla Io
license
Apache-2.0
tags
ai, huggingface, llms, openai, python, rlaif, rlhf, synthetic-data, synthetic-dataset-generation

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
other

πŸ“Š Engagement & Metrics

downloads
0
stars
3,303
forks
246

Data indexed from public sources. Updated daily.