Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:3
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use DeeAteTee/my-embedding-gemma-1st-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DeeAteTee/my-embedding-gemma-1st-test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DeeAteTee/my-embedding-gemma-1st-test") 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
File size: 132 Bytes
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