Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:101762
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use palusi/sentest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use palusi/sentest with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("palusi/sentest") sentences = [ "Why am I still afraid of the dark?", "What one single change can change a life?", "Why do we have a dark side?", "Why are humans afraid of the dark?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, step 5000
Verified signatureba2413c -
Training in progress, step 4000
Verified signature3efa08b -
Training in progress, step 3000
Verified signaturec336a5e -
Training in progress, step 2000
Verified signature2f26ba9 -
Training in progress, step 1000
Verified signaturec7b6294