Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:21484
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use codersan/validadted_FaLabse_onV8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use codersan/validadted_FaLabse_onV8b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codersan/validadted_FaLabse_onV8b") 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:
- 48b3bcbc2c8cf2926e935439f51286b85a86320561306b788b6c04b6e6aa9104
- Size of remote file:
- 2.36 MB
- SHA256:
- 2bb9c2b729f270272e7b3b90f4c181fd841673f082bbb9d1cb20fbe6ca5522f3
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