Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:500
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Aathi13/finetuned-biencoder-campusbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Aathi13/finetuned-biencoder-campusbot with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Aathi13/finetuned-biencoder-campusbot") sentences = [ "Can I get academic adjustments for mental health reasons?", "Yes, appropriate academic accommodations can be arranged through the disability services office with documentation from mental health professionals.", "Yes, many companies conduct online aptitude tests, coding challenges, or domain-specific assessments as part of their selection process.", "The hostel offers Wi-Fi, mess services, laundry, and recreational areas." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle