Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:3094
loss:MultipleNegativesRankingLoss
Instructions to use shogoorg/my-embedding-gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shogoorg/my-embedding-gemma with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shogoorg/my-embedding-gemma") sentences = [ "query: confined-animal-facility", "Sector: agriculture. Subsector: cropland-fires.", "Sector: forestry-and-land-use. Subsector: forest-land-fires.", "Sector: agriculture. Subsector: enteric-fermentation-cattle-operation." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!