Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:100000
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use SMARTICT/gte-small-finetune-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SMARTICT/gte-small-finetune-test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SMARTICT/gte-small-finetune-test") sentences = [ "A man is jumping unto his filthy bed.", "A young male is looking at a newspaper while 2 females walks past him.", "The bed is dirty.", "The man is on the moon." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 201 Bytes
532b6f9 | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "3.0.1",
"transformers": "4.42.4",
"pytorch": "2.4.0+cu121"
},
"prompts": {},
"default_prompt_name": null,
"similarity_fn_name": null
} |