Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:522
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use rchrdgwr/finetuned-arctic-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rchrdgwr/finetuned-arctic-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rchrdgwr/finetuned-arctic-model") sentences = [ "How did the hiring tool's design contribute to the rejection of women applicants?", "legal protections. Throughout this framework the term “algorithmic discrimination” takes this meaning (and \nnot a technical understanding of discrimination as distinguishing between items). \nAUTOMATED SYSTEM: An \"automated system\" is any system, software, or process that uses computation as \nwhole or part of a system to determine outcomes, make or aid decisions, inform policy implementation, collect \ndata or observations, or otherwise interact with individuals and/or communities. Automated systems \ninclude, but are not limited to, systems derived from machine learning, statistics, or other data processing \nor artificial intelligence techniques, and exclude passive computing infrastructure. “Passive computing", "communities. \n• An automated system using nontraditional factors such as educational attainment and employment history as\npart of its loan underwriting and pricing model was found to be much more likely to charge an applicant whoattended a Historically Black College or University (HBCU) higher loan prices for refinancing a student loanthan an applicant who did not attend an HBCU. This was found to be true even when controlling for\nother credit-related factors.32\n•A hiring tool that learned the features of a company's employees (predominantly men) rejected women appli -\ncants for spurious and discriminatory reasons; resumes with the word “women’s,” such as “women’s\nchess club captain,” were penalized in the candidate ranking.33", "dures before deploying the system, as well as responsibility of specific individuals or entities to oversee ongoing assessment and mitigation. Organizational stakeholders including those with oversight of the business process or operation being automated, as well as other organizational divisions that may be affected due to the use of the system, should be involved in establishing governance procedures. Responsibility should rest high enough in the organization that decisions about resources, mitigation, incident response, and potential rollback can be made promptly, with sufficient weight given to risk mitigation objectives against competing concerns. Those holding this responsibility should be made aware of any use cases with the" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K