Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:21484
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use codersan/FaLabseV14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use codersan/FaLabseV14 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codersan/FaLabseV14") sentences = [ "زنی ماهی را سرخ می کند.", "ماهی توسط زنی پخته می شود", "در سال ۱۱۵۷ ق.م کوتیر-ناهوته حکمران ایلام برای گرفتن انتقام بابل را فتح میکند.", "دو نفر سوار موتورسیکلت می شوند" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 205 Bytes
0565c35 | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "3.3.1",
"transformers": "4.47.0",
"pytorch": "2.5.1+cu121"
},
"prompts": {},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |