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tasal9/Multilingual-ZamAI-Embeddings
Multilingual-ZamAI-Embeddings is a sentence similarity model from tasal9. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as apache-2.0.
Task: sentence-similarity / feature-extraction Languages: multilingual, ps, en, ar, fa, ur
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From the Hugging Face model README
Task: sentence-similarity / feature-extraction
Languages: multilingual, ps, en, ar, fa, ur
This model is part of the ZamAI Pashto language AI collection. It is fine-tuned/adapted for sentence-similarity / feature-extraction in Pashto and related languages.
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("tasal9/Multilingual-ZamAI-Embeddings")
sentences = ["دا یو جمله ده.", "This is a sentence.", "له تا څخه مننه"]
embeddings = model.encode(sentences)
print(embeddings.shape)
Training dataset details will be added here.
| Metric | Value | Description |
|---|---|---|
| cosine_similarity | TBD | Add measured value |
| spearman_correlation | TBD | Add measured value |
Update this table with your measured results and link to the evaluation script/notebook.
@misc{zamai_pashto,
title = {{Multilingual ZamAI Embeddings}},
author = {ZamAI / Yaqoob Tasal},
year = {2024},
howpublished = {\url{https://huggingface.co/tasal9/Multilingual-ZamAI-Embeddings}}
}
This model is released under the "apache-2.0" license.