Text Retrieval
sentence-transformers
Safetensors
Amharic
xlm-roberta
sentence-similarity
feature-extraction
Generated from Trainer
dataset_size:122938
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use rasyosef/embedding-amharic-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/embedding-amharic-medium with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rasyosef/embedding-amharic-medium") sentences = [ "በኢትዮጵያ ለመጀመሪያ ጊዜ ወታደራዊ ስልጠና የወሰዱ ዕጩ ዲፕሎማቶች ተመረቁ", "የውጭ ጉዳይ ሚኒስቴር ከሜጀር ጄነራል ሀየሎም አርአያ ወታደራዊ አካዳሚ ጋር በመተባበር በኢትዮጵያ ለመጀመሪያ ጊዜ ወታደራዊ ስልጠና የወሰዱ ዲፕሎማቶችን አስመረቀ፡፡በወታደራዊ አካዳሚው ትላንት በተካሄደ የምርቃት ሥነ- ስርዓት ስልጠናውን ላገኙ 89 ዕጩ ድፕሎማቶች የምስክር ወረቀት ተበረክቷል።", "አዲስ አበባ፣ የካቲት 19፣ 2012 (ኤፍ.ቢ.ሲ) የኢፌዴሪ አየር ኃይል ለከፍተኛ መኮንኖች የማዕረግ እድገት ሰጥቷል።አየር ኃይሉ በዛሬው እለት በቢሾፍቱ በሚገኘው የኢፌዴሪ አየር ኃይል ጠቅላይ መምሪያ ባካሄደው ስነ ስርዓት ላይ የኢፌዴሪ ጦር ኃይሎች ምክተል ኤታማዦር ሹም ጄኔራል ብርሃኑ ጁላ እና የኢፌዴሪ አየር ኃይል ዋና አዛዥ ሜጀር ጄኔራል ይልማ መርዳሳን ጨምሮ ከፍተኛ አመራሮች ተገኝተዋል።በስነ ስርዓቱ ላይ 106 ለሚሆኑ መኮንኖች በአየር ኃይል ዋና አዛዥ ሜጀር ጄኔራል ይልማ መርዳሳ የተለያዩ የማዕረግ እድገቶችን ሰጥተዋል።" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Add paper and code links, update pipeline tag
#1
by nielsr HF Staff - opened
Hi, I'm Niels from the Hugging Face community team.
I'm opening this PR to improve the documentation of this model. Based on the associated paper and GitHub repository, I've:
- Updated the
pipeline_tagtotext-retrievalfor better discoverability in the context of information retrieval. - Added a link to the paper: "The Multilingual Curse at the Retrieval Layer: Evidence from Amharic".
- Added a link to the official GitHub repository.
- Added the BibTeX citation.
Feel free to merge this if it looks good to you!
rasyosef changed pull request status to merged