Sentence Similarity
sentence-transformers
Safetensors
Turkish
xlm-roberta
feature-extraction
semantic-search
information-retrieval
turkish
matryoshka-embeddings
variable-dimensions
hard-negatives
mrl
Eval Results (legacy)
text-embeddings-inference
Instructions to use GoktugD/DUSUNEN-Atlas-278M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GoktugD/DUSUNEN-Atlas-278M-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GoktugD/DUSUNEN-Atlas-278M-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44200fb99ff326e8a2858f9ce344dfdea9c0738bb054a91e24780b1d2e98064c
- Size of remote file:
- 556 MB
- SHA256:
- 66c65d4109a646d3f8a6dc6c19b20efda4d9c5ed9cd5054386812da0d6b263dd
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