Sentence Similarity
sentence-transformers
ONNX
Safetensors
Turkish
English
modernbert
feature-extraction
information-retrieval
dense-retrieval
turkish
legal
turkish-legal
mecellem
TRUBA
MN5
text-embeddings-inference
Instructions to use newmindai/Mursit-Base-TR-Retrieval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use newmindai/Mursit-Base-TR-Retrieval with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("newmindai/Mursit-Base-TR-Retrieval") 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] - Inference
- Notebooks
- Google Colab
- Kaggle

- Xet hash:
- de62d1d90ac618ff6a790a03d579f57024fd55420a42a6be1b472d0ff49c8277
- Size of remote file:
- 156 kB
- SHA256:
- 35d74a68a424786e7eca5fe891553cb3a1cd162e9a972f3e0ab3a125e9280137
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