# LoRA Efficient Fine-tuning

A large Arabic logical reasoning model fine-tuned based on Qwen3-14B, optimized for Arabic logic and deductive reasoning while retaining general conversational capabilities.

DriveLMM-o1 is a fine-tuned large multimodal model optimized for autonomous driving, based on the InternVL2.5-8B architecture and adapted using LoRA technology, achieving step-by-step reasoning through stitched multi-view images.

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

LuxLlama is a fine-tuned version of the Meta-Llama-3.1-8B-Instruct model, specifically optimized for Luxembourgish language understanding and generation, as well as general and mathematical reasoning capabilities.

This model is a Text2Cypher model fine-tuned based on google/gemma-2-9b-it, capable of converting natural language questions into Cypher query statements for Neo4j graph databases.

This is an OpenVLA 7B vision-language-action model fine-tuned using LoRA technology on the LIBERO-Goal dataset, suitable for the robotics field.

This is a vision-language-action model fine-tuned using LoRA on the LIBERO-Object dataset, specifically designed for robotics.