Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
Generated from Trainer
dataset_size:5022
loss:ContrastiveLoss
text-embeddings-inference
Instructions to use samsartor/connections-categories-qwen3-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use samsartor/connections-categories-qwen3-0.6B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("samsartor/connections-categories-qwen3-0.6B") sentences = [ "first words in rappers’ names", "twin, ruby, fire truck, stop sign", "hippo, warthog, heck, fudge", "national, business, taboo, opinion" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K