Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
patent
embeddings
mteb
text-embeddings-inference
Instructions to use datalyes/patembed-base_long_4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use datalyes/patembed-base_long_4096 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("datalyes/patembed-base_long_4096") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4a87b17390e535997a61e1acd9478d489060730473fe3e8b178b9801c96c047
- Size of remote file:
- 596 MB
- SHA256:
- aaeae2209ce6dbbf1cb852fbb044e2b3ca07485b4eefb908af6da51cc3116722
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