Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use ys7yoo/sbert_alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ys7yoo/sbert_alpha with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ys7yoo/sbert_alpha") 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 ys7yoo/sbert_alpha with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ys7yoo/sbert_alpha") model = AutoModel.from_pretrained("ys7yoo/sbert_alpha", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7167c0b21dc5935150842197eb35eec6fbbd503f18583b4fc1516fdd2d8c8140
- Size of remote file:
- 443 MB
- SHA256:
- 1caa8be55692b4c35270831e8c8bd6bb05245789014c20770c1ecc75155ef925
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