Distilabel
Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.
Distilabel scores 4.7/10 (Emerging) in Fine-Tuning.
Language Python License Apache-2.0 Stars 3.3k★ Type library Self-host Yes Repo argilla-io/distilabel Homepage https://distilabel.argilla.io
Quality
Emerging 4.7
Adoption 38
Activity 20
Maturity 95
Community 36
Capability 50
Show the math
Overall 4.7/10
value = 4.7/10
score = value
Adoption 4.4/10
value = 38/100
score = 1 + 9 * value / 100
Activity 2.8/10
value = 20/100
score = 1 + 9 * value / 100
Maturity 9.5/10
value = 94.7/100
score = 1 + 9 * value / 100
Community 4.2/10
value = 35.8/100
score = 1 + 9 * value / 100
Capability 5.5/10
value = 50/100
score = 1 + 9 * value / 100
Key metrics
3.3k★ GitHub stars
0/90d Recent commits
0 devs/90d Recent contributors
2.7y Project age
active Last commit
Gotchas
No gotchas documented yet. Contribute one if you know a constraint we missed.
Labels
- Self-hosted
Self-hosted
You deploy and operate it yourself; there is no hosted option here.
synthetic-data data-generation preference-data pipelines alignment