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_onV8d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use codersan/validadted_FaLabse_onV8d with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codersan/validadted_FaLabse_onV8d") 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
Download training_args.bin from codersan/validadted_FaLabse_onV8d: direct link, hf CLI and curl.
- Browser
- Download file 5.62 kB
-
https://huggingface.co/codersan/validadted_FaLabse_onV8d/resolve/main/training_args.bin
- Command line
-
hf download hf://codersan/validadted_FaLabse_onV8d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codersan/validadted_FaLabse_onV8d/resolve/main/training_args.bin
5.62 kB
- Xet hash:
- e76e1a4292a9d10e4ededf642997e1ad74ee9c189cbf3bac5ae86d58fcf9bfbf
- Size of remote file:
- 5.62 kB
- SHA256:
- 890e0ecee837800bc42fcf4a3a7df61e7bb8faf980d163c730fb54743bcbe4fd
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