# NLI fine-tuning

A zero-shot classification model fine-tuned from MoritzLaurer/deberta-v3-base-zeroshot-v2.0-c using the SmartShot method with an NLI framework

A zero-shot classification model fine-tuned based on roberta-base-zeroshot-v2.0-c, enhanced with SmartShot method and synthetic data

This is a sentence-transformers model fine-tuned from intfloat/multilingual-e5-small, designed to map sentences and paragraphs into a 384-dimensional dense vector space, supporting tasks like semantic textual similarity and semantic search.

This is a small BERT model based on Turkish, specifically designed for vector representations of sentences and paragraphs, suitable for tasks such as clustering and semantic search.

A sentence transformer trained on the BLOOM-1.7B model, specializing in sentence similarity and natural language inference tasks

Zero-shot classification model based on BART-large architecture, fine-tuned on MultiNLI dataset

SGPT-5.8B is a sentence transformer model based on a 5.8B parameter scale, optimized through weighted mean and NLI (Natural Language Inference) fine-tuning, specifically designed for sentence similarity calculation and feature extraction tasks.