Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
dense
Generated from Trainer
dataset_size:10000000
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use seanfarrell/pettag_emed_train_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use seanfarrell/pettag_emed_train_test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seanfarrell/pettag_emed_train_test") sentences = [ "suntan", "mpox", "Suntan", "acne rosacea" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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