Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
embeddings
semantic-search
pashto
zamai
language:multilingual
language:ps
language:en
language:ar
language:fa
language:ur
text-embeddings-inference
Instructions to use tasal9/Multilingual-ZamAI-Embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tasal9/Multilingual-ZamAI-Embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tasal9/Multilingual-ZamAI-Embeddings") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
File size: 242 Bytes
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"name": "0",
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