Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:419
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use wtfharsh144Pandey/aidwise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use wtfharsh144Pandey/aidwise with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("wtfharsh144Pandey/aidwise") sentences = [ "Refugees from Afghanistan seeking primary education for their children", "Sales executive marketing intern accountant", "Refugee education coordinator ESL teacher primary school tutor", "Economics student data entry operator commerce student" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle