Sentence Similarity
sentence-transformers
Safetensors
English
bert
biencoder
text-classification
sentence-pair-classification
semantic-similarity
semantic-search
retrieval
reranking
Generated from Trainer
dataset_size:9233417
loss:ArcFaceInBatchLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use redis/langcache-embed-experimental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use redis/langcache-embed-experimental with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("redis/langcache-embed-experimental") sentences = [ "Hayley Vaughan portrayed Ripa on the ABC daytime soap opera , `` All My Children `` , between 1990 and 2002 .", "Traxxpad is a music application for Sony 's PlayStation Portable published by Definitive Studios and developed by Eidos Interactive .", "Between 1990 and 2002 , Hayley Vaughan Ripa portrayed in the ABC soap opera `` All My Children `` .", "Between 1990 and 2002 , Ripa Hayley portrayed Vaughan in the ABC soap opera `` All My Children `` ." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 283 Bytes
5d42065 c5a2570 5d42065 7fe55cc 5d42065 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"__version__": {
"sentence_transformers": "5.1.0",
"transformers": "4.56.0",
"pytorch": "2.8.0+cu128"
},
"model_type": "SentenceTransformer",
"prompts": {
"query": "",
"document": ""
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |