Sentence Similarity
sentence-transformers
Safetensors
German
llama
text-embeddings
german
retrieval
lora
embedding-model
Eval Results (legacy)
text-embeddings-inference
Instructions to use mayflowergmbh/smollm3-3b-german-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mayflowergmbh/smollm3-3b-german-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mayflowergmbh/smollm3-3b-german-embed") sentences = [ "Was ist die Hauptstadt von Deutschland?", "Berlin ist die Hauptstadt von Deutschland.", "München ist eine Stadt in Bayern.", "Paris ist die Hauptstadt von Frankreich." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 018f31fc20f777567cdd68a5278395430107ccc84a59fbc0aebb67ece1844b48
- Size of remote file:
- 17.2 MB
- SHA256:
- 7b6a500b662a34eb3f0374db856ba4ad7de4c81040571d78dc0d357238930005
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