Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
Generated from Trainer
dataset_size:172562
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Matjac5/MNLP_M3_RAG_MODEL_data_mixture_biology with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Matjac5/MNLP_M3_RAG_MODEL_data_mixture_biology with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Matjac5/MNLP_M3_RAG_MODEL_data_mixture_biology") sentences = [ "The current of a stream runs at the rate of 4 kmph. A boat goes 6 km and back to the starting point in 4 hours, then find the speed of the boat in still water?", ")", "a", "[" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle