Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:5000000
loss:combine_dstilationLoss_studentLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1") sentences = [ "ما هو كور يعني", "تعريف cor . : وحدة قياس سعة عبرية وفينيقية قديمة .", "رفعت منظمة صندوق ادخار الموظفين ( EPFO ) الحد الأدنى للراتب إلى 15000 روبية من 6500 روبية في وقت سابق .", "شكل الجمع بين الجلطة - o يعني _ _ . صيغة الجمع embol - o تعني _ _ . اللاحقة التي تعني أداة قياس الضغط هي _ _ . لاحقة غير كلها تعني صغيرة هي _ _ . اللاحقة التي تعني التصلب هي _ _ ." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download modules.json from hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1: direct link, hf CLI and curl.
- Browser
- Download file 277 Bytes
-
https://huggingface.co/hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1/resolve/22f8c3bed37be148b359a18e5ba34f4aba074857/modules.json
- Command line
-
hf download hf://hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1@22f8c3bed37be148b359a18e5ba34f4aba074857/modules.json
-
curl -L -o modules.json https://huggingface.co/hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1/resolve/22f8c3bed37be148b359a18e5ba34f4aba074857/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" | |
| } | |
| ] |