Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:20469
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use rdxtremity/harrir-bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rdxtremity/harrir-bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rdxtremity/harrir-bge-m3") sentences = [ "运动鞋尺码", "[ELLA] Ruched Diamante Pointy Flats | حذاء فلات مزموم مرصع بالفصوص بمقدمة مدببة. Category: Shoes > Flats & Slip-Ons.", "[Ginger] Classic Crossbody Pink | حقيبة كروس كلاسيكية. Category: Bags > Crossbody Bags.", "[Ipekyol] Monogram Pattern Sneakers | حذاء سنيكرز بنمط مونوغرام. Category: Shoes > Sneakers." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Stage 2 fine-tuning on human search feedback (CosineDistance TripletLoss, lr=1e-5) — 2026-05-19
81013d1 verified | [ | |
| { | |
| "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" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.sentence_transformer.modules.normalize.Normalize" | |
| } | |
| ] |