Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:41454
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use soof/miswag-category-mapper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use soof/miswag-category-mapper with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("soof/miswag-category-mapper") sentences = [ "Bleu Eau De Parfum Men's Perfume عطر بلو للرجال", "Niche Perfumes | عطور النيش | عطور النيش | Beauty > Fragrance > Niche Perfumes | الجمال والعناية > عطور > عطور النيش", "Men Blouses | بلوز رجالي | بلوز رجالي | Clothes, Shoes & Bags > Men Clothes > Men Blouses > Men Blouses | ملابس، أحذية وحقائب > ملابس رجالية > بلوز وتيشرت رجالي > بلوز رجالي", "Men Shoes | حذاء رجالي | حذاء رجالي | Men Fashion > Men Shoes | ملابس رجالية > حذاء رجالي", "Men Niche Perfumes | عطور رجالية | عطور رجالية | Beauty > Fragrance > Niche Perfumes > Men Niche Perfumes | الجمال والعناية > عطور > عطور النيش > عطور رجالية", "Arabian, Oud & Makhmaria | عطور عربية ومخمرية | عطور عربية ومخمرية | Beauty > Fragrance > Arabian, Oud & Makhmaria | الجمال والعناية > عطور > عطور عربية ومخمرية", "Men Fragrance | عطور رجالية | بۆنی پیاوانی | Beauty > Fragrance > Fragrance > Men Fragrance | الجمال والعناية > عطور > العطور > عطور رجالية" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [7, 7] - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": true, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "is_local": false, | |
| "mask_token": "<mask>", | |
| "max_length": 128, | |
| "model_max_length": 128, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<pad>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "</s>", | |
| "stride": 0, | |
| "tokenizer_class": "XLMRobertaTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<unk>" | |
| } | |