Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use pritamdeka/S-PubMedBert-MS-MARCO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pritamdeka/S-PubMedBert-MS-MARCO with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pritamdeka/S-PubMedBert-MS-MARCO") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use pritamdeka/S-PubMedBert-MS-MARCO with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pritamdeka/S-PubMedBert-MS-MARCO") model = AutoModel.from_pretrained("pritamdeka/S-PubMedBert-MS-MARCO") - Inference
- Notebooks
- Google Colab
- Kaggle
The model has apache-2.0 license tag, does that mean this model can be used for Commercial purpose?
#9
by TheBurgmaster - opened
The model has apache-2.0 license tag, does that mean this model can be used for Commercial purpose? Asking because https://microsoft.github.io/msmarco/ claims "The MS MARCO datasets are intended for non-commercial research purposes only".
@TheBurgmaster If that is the situation, then I don't think the model can be used for commercial purpose. I have to change the permission for the model I guess.
pritamdeka changed discussion status to closed