Sentence Similarity
sentence-transformers
PyTorch
Transformers
distilbert
feature-extraction
text-embeddings-inference
Instructions to use jplu/adel-dbpedia-retrieval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jplu/adel-dbpedia-retrieval with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jplu/adel-dbpedia-retrieval") 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 jplu/adel-dbpedia-retrieval with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jplu/adel-dbpedia-retrieval") model = AutoModel.from_pretrained("jplu/adel-dbpedia-retrieval") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 546174218f1586d558603f3fb0016cab4cda1ff9c9190df3006822d68e4a19d3
- Size of remote file:
- 265 MB
- SHA256:
- 82e29efff012e8185adfa6d12057b5b18d31641ff70205c44f5e46109e7d14e4
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