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
- Xet hash:
- 5d747ca97fe6e145aef974d51b6921c06a4eed57a0513eb2427235a9af134752
- Size of remote file:
- 17.1 MB
- SHA256:
- e4f7e21bec3fb0044ca0bb2d50eb5d4d8c596273c422baef84466d2c73748b9c
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