Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:9
loss:MultipleNegativesRankingLoss
embeddinggemma-tuning-lab
text-embeddings-inference
Instructions to use Duino/GEM1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Duino/GEM1.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Duino/GEM1.0") sentences = [ "MY_FAVORITE_NEWS", "Discord will require a face scan or ID for full access next month", "Brutalist Southbank Centre Listed", "Frontier AI agents violate ethical constraints 30–50% of time, pressured by KPIs" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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