Sentence Similarity
sentence-transformers
Safetensors
Arabic
English
bert
embeddings
feature-extraction
semantic-similarity
information-retrieval
semantic-search
cross-lingual
arabic
msa
dialect
text-embeddings-inference
Instructions to use OussamaBenSlama/e5-small-dialect2MSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use OussamaBenSlama/e5-small-dialect2MSA with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("OussamaBenSlama/e5-small-dialect2MSA") sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OussamaBenSlama/e5-small-dialect2MSA: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/OussamaBenSlama/e5-small-dialect2MSA/resolve/main/tokenizer.json
- Command line
-
hf download hf://OussamaBenSlama/e5-small-dialect2MSA/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OussamaBenSlama/e5-small-dialect2MSA/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 952174f03b93ed9e19ea539a90be89b05116b6d8fb83abaaaa47f61528df688d
- Size of remote file:
- 17.1 MB
- SHA256:
- fbcc3c7348739d765de2c86fce14c9c5e2dd47696dbb3cfeed294edfc712d8f0
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