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1from sentence_transformers import SentenceTransformer
2
3model = SentenceTransformer("tasal9/Multilingual-ZamAI-Embeddings")
4sentences = ["دا یو جمله ده.", "This is a sentence.", "له تا څخه مننه"]
5embeddings = model.encode(sentences)
6print(embeddings.shape)| 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.
1@misc{zamai_pashto,
2 title = {{Multilingual ZamAI Embeddings}},
3 author = {ZamAI / Yaqoob Tasal},
4 year = {2024},
5 howpublished = {\url{https://huggingface.co/tasal9/Multilingual-ZamAI-Embeddings}}
6}