Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AAUBS/PatentSBERTa_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AAUBS/PatentSBERTa_V2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AAUBS/PatentSBERTa_V2") sentences = [ "A method for wireless charging using magnetic resonance", "Wireless power transfer through inductive coupling", "A new compound for pharmaceutical use in treating diabetes", "A method for data encryption in wireless communication" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use AAUBS/PatentSBERTa_V2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AAUBS/PatentSBERTa_V2") model = AutoModel.from_pretrained("AAUBS/PatentSBERTa_V2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot