Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:21484
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use codersan/e5Fa_small_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use codersan/e5Fa_small_v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codersan/e5Fa_small_v3") 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
- Xet hash:
- 760c6daffbf06881069cfae2a21b30b2225a901b05ae234485fa6e15a5ed00b2
- Size of remote file:
- 471 MB
- SHA256:
- a836803377577c939edcd29ed3e19dbeacd40c2acd25f8fce1c770ed64a2ac9d
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