Sentence Similarity
sentence-transformers
Safetensors
English
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:1521
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use saraleivam/GURU-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use saraleivam/GURU-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("saraleivam/GURU-model") sentences = [ "latency definition", "The Wizard of Oz movie musical premieres in Oconomowoc, Wisconsin. The Wizard of Oz, starring Judy Garland and featuring words and music by E.Y. âYipâ Harburg and Harold Arlen, receives its world premiere in Oconomowoc, Wisconsin, on this day in 1939.", "Latency is a networking term to describe the total time it takes a data packet to travel from one node to another. In other contexts, when a data packet is transmitted and returned back to its source, the total time for the round trip is known as latency.", "Definition - What does Latency mean? Latency is a networking term to describe the total time it takes a data packet to travel from one node to another. In other contexts, when a data packet is transmitted and returned back to its source, the total time for the round trip is known as latency." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle