Feature Extraction
sentence-transformers
Safetensors
multilingual
embedding_gemma2
zen
zen-embedding
zenlm
hanzo
embedding
multimodal-embedding
vision
audio
video
retrieval
matryoshka
Instructions to use zenlm/zen-embedding-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zenlm/zen-embedding-2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zenlm/zen-embedding-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
Commit History
2 days ago
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Zen Embedding 2: EmbeddingGemma 2 (Google DeepMind, Apache-2.0) at 914f7f89, weights unchanged
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