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
| [ | |
| { | |
| "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" | |
| } | |
| ] | |