Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use omarelsayeed/Search_Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use omarelsayeed/Search_Test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("omarelsayeed/Search_Test") 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/Search_Test with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("omarelsayeed/Search_Test") model = AutoModel.from_pretrained("omarelsayeed/Search_Test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61b50b9b487fde2b06aaa58d0bef69e6c4b6e1ca5e242ddaf8f6537b2830c696
- Size of remote file:
- 46.2 MB
- SHA256:
- 5f601e56d02f6b95863ee9b870a7926fc47bf284c9db41550bf117eb447a58f5
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