Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AI-Growth-Lab/PatentSBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AI-Growth-Lab/PatentSBERTa with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AI-Growth-Lab/PatentSBERTa") 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 AI-Growth-Lab/PatentSBERTa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AI-Growth-Lab/PatentSBERTa") model = AutoModel.from_pretrained("AI-Growth-Lab/PatentSBERTa") - Inference
- Notebooks
- Google Colab
- Kaggle
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# PatentSBERTa
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- feature-extraction
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- sentence-similarity
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- transformers
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widgets:
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- text: "A method for wireless charging using magnetic resonance"
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text2: "Wireless power transfer through inductive coupling"
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- text: "A new compound for pharmaceutical use in treating diabetes"
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text2: "A method for wireless charging using magnetic resonance"
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# PatentSBERTa
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