Sentence Similarity
sentence-transformers
Safetensors
new
feature-extraction
Generated from Trainer
dataset_size:498670
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use AhmedZaky1/DIMI-embedding-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AhmedZaky1/DIMI-embedding-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AhmedZaky1/DIMI-embedding-v2", trust_remote_code=True) sentences = [ "كم يبغ عدد السكان في المملكة المتحدة؟", "هناك العديد من الناس الحاضرين.", "كم عدد سكان أوكرانيا؟", "لماذا باراك أوباما غير مؤهل للترشح في انتخابات الرئاسة لعام 2016؟" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from AhmedZaky1/DIMI-embedding-v2: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/AhmedZaky1/DIMI-embedding-v2/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://AhmedZaky1/DIMI-embedding-v2/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/AhmedZaky1/DIMI-embedding-v2/resolve/main/config_sentence_transformers.json
205 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "3.3.1", | |
| "transformers": "4.51.3", | |
| "pytorch": "2.6.0+cu124" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |