Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
Embedding
RAG
Logical-Embedding
text-embeddings-inference
Instructions to use realAABeigi/ZAT-E1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use realAABeigi/ZAT-E1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("realAABeigi/ZAT-E1") sentences = [ "The sign says the ice is very thin and skating is strictly forbidden.", "If you go out on the lake, you will likely fall through and get hurt.", "The sign says the ice is not thin and skating is not strictly forbidden." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
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