Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:100000
loss:GISTEmbedLoss
text-embeddings-inference
Instructions to use carsondial/slinger-single-word with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use carsondial/slinger-single-word with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("carsondial/slinger-single-word") sentences = [ "Brass decorative stampings including a number of ornamental frames. Some brass frames made specifically to accept\nSwarovski ss30 flat back stones.\n508-222-2000 Fax 508-222-3011 Email firstname.lastname@example.org\nBrothers brass jewelry findings are open line and\nMade in USA\n(c) 2003-2017 Guyot Brothers Co Inc, A jewelry findings manufacturer", "Mining", "Findings", "rug" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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