Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:710
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use bau0221/ptz_embedding_ver3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bau0221/ptz_embedding_ver3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bau0221/ptz_embedding_ver3") sentences = [ "Set Camera 4 to follow Ava at the top side", "Camera 4 put Grace on the top side", "Set Camera 3 to put Michael at the bottom side", "Set Wyatt at the left side on group1" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle