Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:167423
loss:MSELoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use omarabb315/makeML-snowflake with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use omarabb315/makeML-snowflake with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("omarabb315/makeML-snowflake") sentences = [ "مجموعة 5 قطع من حلي الأكواب من باندورا", "Dark Blue High Waist Mom Jeans TWOAW24JE00041", "Pandora 5 Pc Drink Charms", "Kancan Women's Stretchy Maternity Bermuda Shorts | Amber & Ivory Boutique 3/25 " ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 297 Bytes
3815ada | 1 2 3 4 5 6 7 8 9 10 | {
"word_embedding_dimension": 1024,
"pooling_mode_cls_token": true,
"pooling_mode_mean_tokens": false,
"pooling_mode_max_tokens": false,
"pooling_mode_mean_sqrt_len_tokens": false,
"pooling_mode_weightedmean_tokens": false,
"pooling_mode_lasttoken": false,
"include_prompt": true
} |