sentence-transformers How to use JoeNoss1998/Noss with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("JoeNoss1998/Noss")
sentences = [
"How can bias testing influence the design and launch of automated systems?",
"reinforce those legal protections but extend beyond them to ensure equity for underserved communities48 \neven in circumstances where a specific legal protection may not be clearly established. These protections \nshould be instituted throughout the design, development, and deployment process and are described below \nroughly in the order in which they would be instituted. \nProtect the public from algorithmic discrimination in a proactive and ongoing manner \nProactive assessment of equity in design. Those responsible for the development, use, or oversight of",
"the severity of certain diseases in Black Americans. Instances of discriminatory practices built into and \nresulting from AI and other automated systems exist across many industries, areas, and contexts. While automated \nsystems have the capacity to drive extraordinary advances and innovations, algorithmic discrimination \nprotections should be built into their design, deployment, and ongoing use. \nMany companies, non-profits, and federal government agencies are already taking steps to ensure the public \nis protected from algorithmic discrimination. Some companies have instituted bias testing as part of their product \nquality assessment and launch procedures, and in some cases this testing has led products to be changed or not",
"accuracy), and enable human users to understand, appropriately trust, and effectively manage the emerging \ngeneration of artificially intelligent partners.95 The National Science Foundation’s program on Fairness in \nArtificial Intelligence also includes a specific interest in research foundations for explainable AI.96\n45"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
