Sentence Similarity
sentence-transformers
Safetensors
English
feature-extraction
dense
Generated from Trainer
dataset_size:106628
loss:MultipleNegativesRankingLoss
Instructions to use samuerio/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use samuerio/lora_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("samuerio/lora_model") sentences = [ "ace-v", "The floor plan was drafted at 1/4 inch scale where each quarter inch equals one foot.", "Fingerprint examiners follow the ACE-V methodology for identification.", "Most modern streaming services offer content in 1080p full HD quality." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16cbf530126b54bedd94c495093938bebec34ed6974f5d919d75d15edcbdd85f
- Size of remote file:
- 11.4 MB
- SHA256:
- 8e0233be851394880d4a610f3f8e337e92fc37fcbf9a8d3f092d1b03dd5a8bdd
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