Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
embeddinggemma
code-search
matryoshka
fine-tuned
text-embeddings-inference
Instructions to use jasperan/embeddinggemma-code-search with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jasperan/embeddinggemma-code-search with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jasperan/embeddinggemma-code-search") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3741258211635609f205bc25b71c9fbe0083510d17e9d729b081bf87ee3436ac
- Size of remote file:
- 1.21 GB
- SHA256:
- e13b29fe9043be123e22ab507217f1d41458e09df3b732eb2c68d6b2712f1986
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