Sentence Similarity
sentence-transformers
Safetensors
Bashkir
gemma3_text
trimmed
text-embeddings-inference
Instructions to use alphaedge-ai/embeddinggemma-bak-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/embeddinggemma-bak-32768 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/embeddinggemma-bak-32768") 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:
- c13986d219092feca9974fa81a7f2547549588c084dbd4d95a9f8e74844884bc
- Size of remote file:
- 507 MB
- SHA256:
- 5ec6c3e26c20578b6fada4a6785957ccba223555e08b47d7f6d0f2b6b1abd3a8
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