Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:8960
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use JW451609703/bar-de-bitext-bge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JW451609703/bar-de-bitext-bge with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JW451609703/bar-de-bitext-bge") sentences = [ "De oanzige Räuberbande hod de Buam vom Dorf ois g'numma.", "Tom und Maria hatten im Urlaub eine gute Zeit.", "Der TOEIC fand wie üblich statt.", "Diese gemeine Räuberbande hat den Bauern des Dorfes alles genommen." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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