Sentence Similarity
sentence-transformers
Safetensors
Turkish
bert
feature-extraction
Generated from Trainer
dataset_size:1416892
loss:SoftmaxLoss
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use x1saint/gte-small-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use x1saint/gte-small-tr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("x1saint/gte-small-tr") sentences = [ "answers-forums", "main-forums", "2015", "\"Yaklaşan kozmik dinlenme çerçevesine göre ... 371 km / s hızla Aslan takımyıldızına doğru\" hareket ediyoruz.", "0117", "Başka bir nesneye göre olmayan bir 'hareketsiz' yoktur.", "0.80" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [7, 7] - Notebooks
- Google Colab
- Kaggle
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| } | |
| ] |