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seo-embedding-uczciweseo
Kelnux/seo-embedding-uczciweseo
seo-embedding-uczciweseo is a sentence similarity model from Kelnux. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as mit.
Model embeddingowy fine-tuned dla polskiego rynku SEO, wytrenowany na: - cyberandy/seo-grpo-reasoning-dataset-1000 - dataset SEO reasoning - UczciweSEO.pl - polskie dane SEO - Terminologia seovoc/schema.org
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At a glance
- Task
- Sentence Similarity
- Library
- sentence-transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Feb 4, 2026
- Updated
- Feb 5, 2026
- SHA
- bf8e5afa
Base models
Model card
From the Hugging Face model README
SEO Embedding Model - UczciweSEO.pl v2
Model embeddingowy fine-tuned dla polskiego rynku SEO, wytrenowany na:
- cyberandy/seo-grpo-reasoning-dataset-1000 - dataset SEO reasoning
- UczciweSEO.pl - polskie dane SEO
- Terminologia seovoc/schema.org
Wyniki
| Metryka | v1 | v2 | Zmiana |
|---|---|---|---|
| Pary podobne | 0.7762 | 0.8229 | +0.047 |
| Pary różne | 0.3309 | 0.2982 | -0.033 |
| Gap (separacja) | 0.4453 | 0.5247 | +0.079 |
Użycie
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Kelnux/seo-embedding-uczciweseo")
# Generuj embeddingi
sentences = ["technical SEO audit", "audyt techniczny strony"]
embeddings = model.encode(sentences)
# Oblicz podobieństwo
from sklearn.metrics.pairwise import cosine_similarity
similarity = cosine_similarity([embeddings[0]], [embeddings[1]])[0][0]
print(f"Podobieństwo: {similarity:.4f}")
Przykłady
| Fraza 1 | Fraza 2 | Podobieństwo |
|---|---|---|
| technical SEO audit steps | crawl errors in Google Search Console | 0.79 |
| structured data | dane strukturalne schema.org | 0.93 |
| organic traffic | ruch organiczny | 0.91 |
| keyword difficulty | long-tail keywords | 0.88 |
Specyfikacja
- Wymiar: 384
- Base model: paraphrase-multilingual-MiniLM-L12-v2
- Dane treningowe: 298 par (SEO-GRPO + UczciweSEO + terminologia)
- Języki: polski, angielski
Kategorie treningowe
- Technical SEO (crawl issues, indexing)
- Content SEO (keywords, optimization)
- Link building (internal linking, anchor text)
- seovoc/schema.org concepts
- UczciweSEO terminology (uczciwe praktyki SEO)
Citation
@misc{seo-embedding-uczciweseo,
title={SEO Embedding Model for UczciweSEO.pl},
year={2025},
publisher={HuggingFace},
url={https://huggingface.co/Kelnux/seo-embedding-uczciweseo}
}
- Task
- Sentence Similarity
- Library
- sentence-transformers
- Type
- bert
- License
- mit
- Languages
- pl, en
- Created
- Feb 4, 2026
- Updated
- Feb 5, 2026