Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:40000
loss:MSELoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use aloizidis/make-multilingual-en-lb-checkpoint-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use aloizidis/make-multilingual-en-lb-checkpoint-5000 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aloizidis/make-multilingual-en-lb-checkpoint-5000") sentences = [ "Who is filming along?", "Wién filmt mat?", "Weider huet den Tatarescu drop higewisen, datt Rumänien durch seng krichsbedélegong op de 6eite vun den allie'erten 110.000 mann verluer hätt.", "Brambilla 130.08.03 St." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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