Sentence Similarity
sentence-transformers
Safetensors
English
feature-extraction
Generated from Trainer
dataset_size:4373977
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use LocalWisdom/PurpleStatic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LocalWisdom/PurpleStatic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LocalWisdom/PurpleStatic") sentences = [ "crack", "master", "Academic journals often publish both print editions and digital versions simultaneously.", "ceramic ware" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 284 Bytes
6b2fbf2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"__version__": {
"pytorch": "2.13.0+cu130",
"sentence_transformers": "5.6.1",
"transformers": "5.14.1"
},
"default_prompt_name": null,
"model_type": "SentenceTransformer",
"prompts": {
"document": "",
"query": ""
},
"similarity_fn_name": "cosine"
} |