sentence-transformers
Safetensors
English
bert
medembed
medical-embedding
clinical-embedding
information-retrieval
Instructions to use abhinand/MedEmbed-base-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use abhinand/MedEmbed-base-v0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("abhinand/MedEmbed-base-v0.1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Link to training dataset
#1
by ben-epstein - opened
Nice work! Is this the dataset you trained with? https://huggingface.co/datasets/abhinand/clini-colbert-pairs-dev-v2
I see it referenced in the codebase but nowhere official
Hi @ben-epstein I'll release the data soon...just a few things to tidy up. The clini-colbert-pairs-dev-v2 is just an experimental version, I'll release the full data in a day or two.
Updated the training dataset @ben-epstein
https://huggingface.co/datasets/abhinand/MedEmbed-training-triplets-v1
Closing this!
abhinand changed discussion status to closed