Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use omarelsayeed/QA_Search_E5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use omarelsayeed/QA_Search_E5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("omarelsayeed/QA_Search_E5") 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 omarelsayeed/QA_Search_E5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("omarelsayeed/QA_Search_E5") model = AutoModel.from_pretrained("omarelsayeed/QA_Search_E5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36ab9f3ef01f44795b6d044087cb1213ec0c21cdd4b68e0e42eac2466a05a8e8
- Size of remote file:
- 838 kB
- SHA256:
- e852f89dc047b37115597d63437977dde03e8e41e6fc8bdbc42901103b63394b
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