How to use Thunder421/criterion-finetuned-bert with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Thunder421/criterion-finetuned-bert") sentences = [ "Lead Data Scientist bringing over 8 years of industry experience along with a verified Masters degree. Expert competencies cover Python data ecosystems, custom Pandas metrics, NumPy, and advanced SQL matrices. Proven success track record in building high-dimension feature distributions to trace underlying statistical variations.", "Seeking a skilled Algo-Trading Research Associate to join our growing team. Key responsibilities include modeling volatile financial vectors to predict historical risk exposure trends. Must be fully comfortable handling tools like Time-series variance tracking analytics, econometric models, and asset liquidity formulas in a fast-paced environment.", "We are looking for a Infrastructure Platform Architect with a minimum of 4+ years of experience. The core technical stack requirements involve deep knowledge in: OCI Containers, Container Orchestration Engine, AWS Cloud Platform, Terraform, Python3. Must be highly capable of executing product deliverables in a fast paced workspace environment.", "Seeking a skilled Senior iOS/Android Mobile Developer to join our growing team. Key responsibilities include managing offline caching synchronization pipelines and publishing builds across app marketplaces. Must be fully comfortable handling tools like Swift UI frameworks, core mobile animations, Kotlin, and Gradle scripts in a fast-paced environment." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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