Sentence Similarity
sentence-transformers
Safetensors
English
qwen3
feature-extraction
dense
Generated from Trainer
dataset_size:232965
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use RohitUltimate/Qwen3-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RohitUltimate/Qwen3-0.6B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RohitUltimate/Qwen3-0.6B") sentences = [ " gbp issued by the surrey oaks surrey june james connolly transaction card", "Food and subsistence", "Other direct costs", "Directors' current accounts" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from RohitUltimate/Qwen3-0.6B: direct link, hf CLI and curl.
- Browser
- Download file 295 Bytes
-
https://huggingface.co/RohitUltimate/Qwen3-0.6B/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://RohitUltimate/Qwen3-0.6B/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/RohitUltimate/Qwen3-0.6B/resolve/main/config_sentence_transformers.json
295 Bytes
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.3.0", | |
| "transformers": "5.3.0", | |
| "pytorch": "2.8.0+cu128" | |
| }, | |
| "prompts": { | |
| "query": "", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |