# Multilingual Q&A

Galactic-Qwen-14B-Exp2 is a large language model based on the Qwen 2.5 14B architecture, focusing on enhanced reasoning capabilities, excelling in context understanding, logical reasoning, and multi-step problem solving.

Serpens-Opus-14B-Exp is a 14-billion-parameter model based on the Qwen 2.5 14B architecture, designed to enhance reasoning capabilities for general-purpose reasoning and Q&A tasks.

A multilingual causal language model fine-tuned based on Lucie-7B, supporting French and English, focused on instruction following and text generation tasks.

Qwen 2.5 0.5B is a compact yet powerful language model, fine-tuned based on Qwen/Qwen2.5-0.5B-Instruct, supporting multiple languages with performance close to the Llama 3.2 1B model.

A Turkish-English bilingual model fine-tuned from unsloth/llama-3-8b-bnb-4bit, optimized for training speed using Unsloth

MMedLM is a multilingual healthcare foundation model with 7 billion parameters, based on the InternLM architecture, pretrained on the comprehensive multilingual medical corpus MMedC.

A question-answering model fine-tuned on the SQuAD dataset based on bert-base-multilingual-cased

A multilingual Q&A model fine-tuned on the xquad dataset based on bert-base-multilingual-cased

A multilingual Q&A model based on mDeBERTa-v3-base, fine-tuned on the SQuAD2.0 dataset

A multilingual Q&A model based on XLM-RoBERTa-large, trained on the XQuAD dataset, supporting extractive Q&A tasks in 11 languages.

A multilingual Q&A model based on XLM-Roberta pre-training, supporting English, Tamil, and Hindi, optimized for Indian language Q&A scenarios

Based on Google's BERT base multilingual model, fine-tuned on Q&A datasets in 11 languages, supporting cross-lingual Q&A tasks

This is a question-answering model fine-tuned on the Stanford Question Answering Dataset (SQuADv1.1) based on the multilingual BERT model, supporting reading comprehension tasks in multiple languages.

An mbart model trained from scratch on an unknown dataset, specific uses and features require further details

This is an xlm-roberta-large model fine-tuned on the SQuADv2 dataset for question answering tasks

A Q&A model fine-tuned on the squad_v2 dataset based on the xlm-roberta-large model

This is a pretrained model based on the XLM-RoBERTa architecture, trained with masked language modeling objectives and fine-tuned on English and Russian question answering datasets.

This model is a multilingual Q&A model fine-tuned on the TyDi QA dataset based on Google's mT5-base, supporting Q&A tasks in 101 languages.