Feature Extraction
sentence-transformers
Safetensors
multilingual
English
qwen3
sentence-similarity
embeddings
mteb
retrieval
bidirectional
text-embeddings-inference
Instructions to use KiteFishAI/Nano-Em1-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KiteFishAI/Nano-Em1-0.6B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KiteFishAI/Nano-Em1-0.6B") 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:
- 5f2b3ceaebd0e4278951cc3b39b5ee44a1f330e275f8ebab2a6a55e118631506
- Size of remote file:
- 11.4 MB
- SHA256:
- 508635c756562e715417f4480d287917c332083cee37d2afca7f9b623fce55d9
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