Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:5749
loss:CosineSimilarityLoss
Eval Results (legacy)
Instructions to use spartan8806/atles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use spartan8806/atles with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("spartan8806/atles") sentences = [ "Red sports car racing down track.", "A red sports car driving quickly on a track.", "Mali's Interim President Sworn Into Office", "Iran, world powers pledge new nuclear talks" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- 1_Pooling
- 2_Dense
- 3_Dense
- Oracle
- atles
- atles_demo
- atles_mobile_app
- config
- configs
- datasets
- docs
- examples
- lib
- models
- tests
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