Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:530
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk") sentences = [ "If you receive a BharatPe speaker that you didn't order, please contact BharatPe support immediately. They will assist in resolving the issue and advise on the next steps.", "Can I control multiple BharatPe speakers from one app?", "What to do if the BharatPe speaker's transaction announcements are intermittently silent?", "What should I do if I receive a BharatPe speaker without ordering it?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!