Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use ahhany/constructionEmbeddingModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ahhany/constructionEmbeddingModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ahhany/constructionEmbeddingModel") 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 ahhany/constructionEmbeddingModel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ahhany/constructionEmbeddingModel") model = AutoModel.from_pretrained("ahhany/constructionEmbeddingModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76ff818b9c658999ce92193c8425ef12b9df646c467c1ab3ba5042dbe6457c1e
- Size of remote file:
- 90.9 MB
- SHA256:
- a36d6f34377630f64647fbcc8b8838b1cab38e8dc95c903c7ff2ac19b521babe
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