Sentence Similarity
sentence-transformers
Safetensors
Swedish
qwen3
feature-extraction
swedish
superlim
mteb
text-embeddings-inference
Instructions to use oxfrug/qwen3-embedding-0.6b-swedish-superlim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use oxfrug/qwen3-embedding-0.6b-swedish-superlim with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("oxfrug/qwen3-embedding-0.6b-swedish-superlim") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
File size: 676 Bytes
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{
"task": "sweparaphrase",
"split": "test",
"n": 1378,
"pearson": 0.8249,
"spearman": 0.8226,
"model": "qwen3-emb-0.6b-sv-soup15",
"hf_id": "/home/daha/pgr/projects/llm-lab/models/students/qwen3-emb-0.6b-sv-soup/w15/final"
},
{
"task": "swefaq",
"split": "test",
"n": 109,
"accuracy": 0.6055,
"n_correct": 66,
"query_prompt": true,
"by_source": {
"Härryda kommun": 0.5,
"Kammarkollegiet": 0.7297,
"Vårdguiden": 0.5441
},
"n_categories": 10,
"model": "qwen3-emb-0.6b-sv-soup15",
"hf_id": "/home/daha/pgr/projects/llm-lab/models/students/qwen3-emb-0.6b-sv-soup/w15/final"
}
]
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