Sentence Similarity
sentence-transformers
Safetensors
Turkish
new
feature-extraction
Generated from Trainer
dataset_size:482091
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
loss:CoSENTLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use newmindai/TurkEmbed4STS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use newmindai/TurkEmbed4STS with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("newmindai/TurkEmbed4STS", trust_remote_code=True) sentences = [ "Ya da dışarı çıkıp yürü ya da biraz koşun. Bunu düzenli olarak yapmıyorum ama Washington bunu yapmak için harika bir yer.", "“Washington's yürüyüş ya da koşu için harika bir yer.”", "H-2A uzaylılar Amerika Birleşik Devletleri'nde zaman kısa süreleri var.", "“Washington'da düzenli olarak yürüyüşe ya da koşuya çıkıyorum.”" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2be16977d9c39b20653b6c69b59b4ac19a93a100dda1e3c813a81b03ce6973f2
- Size of remote file:
- 1.22 GB
- SHA256:
- 5d032a10bdc6dd641ac27e804cd8720f60aef13f30235da48b1a3c11b869eb9d
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