Sentence Similarity
sentence-transformers
Safetensors
Turkish
embedding_gemma2_text
legal
law
turkish
turkish-legal
embeddings
feature-extraction
information-retrieval
dense-retrieval
case-law-retrieval
yargitay
ictihat
gemma
gemma-2
Instructions to use HukukcuApp/tr-legal-embedding-gemma-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HukukcuApp/tr-legal-embedding-gemma-2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HukukcuApp/tr-legal-embedding-gemma-2") 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
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