# Cross-domain Adaptation

This is a sentence-transformers model fine-tuned from allenai/longformer-base-4096, designed to generate 768-dimensional dense vector representations for sentences and paragraphs, suitable for semantic text similarity, semantic search, and related tasks.

This is a multi-model fusion result based on the Qwen2.5-14B architecture, utilizing the Model Stock fusion method, combining 22 different 14B-parameter scale models from various sources.

Linq-Embed-Mistral is an embedding model based on the Mistral architecture, specializing in text classification, retrieval, and clustering tasks, with outstanding performance across multiple MTEB benchmarks.

This is a cross-encoder model fine-tuned from cross-encoder/ms-marco-MiniLM-L6-v2, developed using the sentence-transformers library. It can compute scores for text pairs and is suitable for text re-ranking and semantic search.

This is a transformers model hosted on Hugging Face Hub. Specific functions and uses require further information.

A text summarization model based on the Mistral 7B architecture, optimized for efficiency and performance using LoRA technology.

MiniCPM-Embedding is an embedding model developed based on the MiniCPM-2B-sft-bf16 foundation model, specializing in retrieval tasks and supporting both Chinese and English.

Insufficient model information, unable to provide specific introduction

BAAI/bge-base-en-v1.5 is a Transformer-based English text embedding model, primarily used for sentence similarity calculation and text classification tasks.

This model is based on the Transformers library, and its specific functions and uses require further information for confirmation.

No model information available

This is an open-source model using the Apache-2.0 license, with specific functionalities and application areas requiring further confirmation