Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:358
loss:MultipleNegativesRankingLoss
dataset_size:322
Eval Results (legacy)
text-embeddings-inference
Instructions to use RahulMeganathan/e5-smart-home-private with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RahulMeganathan/e5-smart-home-private with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RahulMeganathan/e5-smart-home-private") sentences = [ "Turn off all thermostats in the house", "All thermostats in the house include device_1: Thermostat in bedroom and device_16: Thermostat in 1st Floor Hallway.", "The study plug is device_7: SmartPlug, Wifi Smart Plug Study, currently off.", "The front door lock is device_15: SmartLock, Door Lock, currently disconnected." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K