Feature Extraction
PyTorch
sentence-transformers
English
pytorch_leaf_cpu
embeddings
text-embeddings
semantic-search
int8-quantized
knowledge-distillation
leaf
embeddinggemma
Instructions to use tss-deposium/gemma300-leaf-embeddings-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tss-deposium/gemma300-leaf-embeddings-test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tss-deposium/gemma300-leaf-embeddings-test") 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
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