Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:521
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use saraleivam/GURU-trained-final-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use saraleivam/GURU-trained-final-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("saraleivam/GURU-trained-final-model") sentences = [ "Advanced TensorFlow and Keras for AI.", "Data analyst with SPSS skills.", "Chef with creative cuisine skills.", "AI developer with TensorFlow and Keras experience." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K