Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:2402
loss:TripletLoss
text-embeddings-inference
Instructions to use jtatman/minilm-L12-H384-psychology with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jtatman/minilm-L12-H384-psychology with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jtatman/minilm-L12-H384-psychology") sentences = [ " A 58-year-old man suffers a stroke and is admitted to a rehabilitation unit for physical therapy. He is unable to wash the left side of his body and denies that his left arm belongs to him even though he clearly visualizes it.", "A", "Examination reveals that the patients somatosensory system is intact. These findings indicate that the patient may have a lesion. In which area of the brain is the lesion?n A. Substantia nigra B. Caudate nucleusn C. Right parietal cortex D. Left parietal cortexn E. Right frontal cortex", "A" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K