Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:287
loss:WeightedCosineSimilarityLoss
text-embeddings-inference
Instructions to use WarTitan2077/Checkins-Ranking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use WarTitan2077/Checkins-Ranking with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("WarTitan2077/Checkins-Ranking") sentences = [ "check-in ai_dev", "Today I fixed some text and text UI for my escape room project, I simplified the explanation of the puzzles as well as changing the look of the dialog boxes", "Delivered new feature set for public release.", "Configured Colab runtime but didn’t run training yet." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle