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
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.2.2", | |
| "transformers": "4.56.2", | |
| "pytorch": "2.9.0+cu126" | |
| }, | |
| "prompts": { | |
| "query": "", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |