Sentence Similarity
sentence-transformers
Safetensors
Arabic
bert
feature-extraction
arabic
embeddings
matryoshka
knowledge-distillation
text-embeddings-inference
Instructions to use masterofaudio2077/Fada_ar_embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use masterofaudio2077/Fada_ar_embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("masterofaudio2077/Fada_ar_embedding") 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 modules.json from masterofaudio2077/Fada_ar_embedding: direct link, hf CLI and curl.
- Browser
- Download file 277 Bytes
-
https://huggingface.co/masterofaudio2077/Fada_ar_embedding/resolve/main/modules.json
- Command line
-
hf download hf://masterofaudio2077/Fada_ar_embedding/modules.json
-
curl -L -o modules.json https://huggingface.co/masterofaudio2077/Fada_ar_embedding/resolve/main/modules.json
277 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.base.modules.transformer.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling" | |
| } | |
| ] |