# Explainable AI

Second-generation reasoning model developed by SmilyAI Labs, featuring a sarcastic antagonist-style AI persona with structured reasoning output

PPACE is an 8-billion-parameter large language model specifically designed for automatic classification of biomedical funding project abstracts, supporting the World Health Organization's research priority classification.

LogicLlama is a fine-tuned language model developed by Goppa AI, based on the 1-billion-parameter version of LLaMA, enhanced with knowledge injection and logical reasoning capabilities, suitable for edge device applications.

ThinkGuard is an advanced guardrail model designed to enhance safety classification capabilities through deliberate slow thinking.

A multimodal foundation model fine-tuned based on LLaVA-Med v1.5 Mistral-7B, optimized for analyzing chest X-ray images and detecting pneumonia

A medical reasoning model fine-tuned based on the DeepSeek-R1-Distill-Llama-8B model, optimized for chain-of-thought reasoning and clinical decision-making capabilities

ConceptCLIP is a large-scale vision-language pre-training model enhanced with medical concepts, suitable for various medical imaging modalities, capable of achieving robust performance across multiple medical imaging tasks.

The first open-source large language model series with instruction-following capability for explainable mental health analysis

MentalBART is a mental health analysis model fine-tuned based on facebook/bart-large, part of the MentaLLaMA project, focusing on explainable mental health analysis.

The first open-source large language model with instruction-following capability for explainable mental health analysis

The first open-source large language model with instruction-following capability for explainable mental health analysis, fine-tuned based on LLaMA2-chat-7B

BERT is a pre-trained language model based on the Transformer architecture, capable of handling various natural language processing tasks in multiple languages.