# Text Re-ranking

This is the result of GPTQ quantization on Qwen/Qwen3-Reranker-4B, significantly reducing VRAM usage.

This is a fine-tuned cross-encoder model based on cross-encoder/ms-marco-MiniLM-L6-v2, primarily used for text re-ranking and semantic search tasks.

A cross-encoder model trained on the msmarco dataset using the sentence-transformers library, designed for text re-ranking and semantic search

This is a cross-encoder model fine-tuned from nreimers/MiniLM-L6-H384-uncased, designed for computing scores of text pairs, suitable for text re-ranking and semantic search tasks.

This is a cross-encoder model fine-tuned from ModernBERT-base for text re-ranking and semantic search tasks.

This is a cross-encoder model fine-tuned from ModernBERT-base, designed for calculating scores of text pairs, suitable for text re-ranking and semantic search tasks.

This is a cross-encoder model fine-tuned on MiniLM-L12-H384-uncased for text re-ranking and semantic search tasks.