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
Download config_sentence_transformers.json from samsartor/connections-categories-qwen3-0.6B: direct link, hf CLI and curl.
- Browser
- Download file 336 Bytes
-
https://huggingface.co/samsartor/connections-categories-qwen3-0.6B/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://samsartor/connections-categories-qwen3-0.6B/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/samsartor/connections-categories-qwen3-0.6B/resolve/main/config_sentence_transformers.json
336 Bytes
| { | |
| "prompts": { | |
| "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine", | |
| "__version__": { | |
| "sentence_transformers": "4.1.0", | |
| "transformers": "4.52.4", | |
| "pytorch": "2.7.1+cu126" | |
| } | |
| } |