Sentence Similarity
sentence-transformers
Safetensors
Swedish
English
eurobert
diabase
embeddings
semantic-search
retrieval
rag
swedish
european-ai
sovereign-ai
custom_code
Instructions to use Diabase/embedding-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Diabase/embedding-1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Diabase/embedding-1", trust_remote_code=True) 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:
- 9d40c9d808a768a5d0ef2b54932dc0f5e568abc6d678732931743515f6948bf7
- Size of remote file:
- 17.2 MB
- SHA256:
- 2f8d233bdf990d8cf166ce63a884dc3f368f4300f18c4b35ae32df15b7d0387d
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