# Long-text processing

This is an INT8-quantized Mistral-Small-3.1-24B-Instruct-2503 model, optimized by Red Hat and Neural Magic, suitable for fast response and low-latency scenarios.

This is a 24B-parameter conditional generation model based on the Mistral3 architecture, optimized with FP8 dynamic quantization, suitable for multilingual text generation and visual understanding tasks.

Yi-1.5 is an upgraded version of the Yi model, excelling in programming, mathematics, reasoning, and instruction-following capabilities while maintaining excellent language understanding, commonsense reasoning, and reading comprehension.

A Chinese-English bilingual large language model jointly open-sourced by DeepLang Tech and Tsinghua NLP Lab, pre-trained on trillions of high-quality tokens with 8K context window processing capability

A 65B-parameter instruction-tuned large language model developed by Upstage based on the LLaMA architecture, supporting long-text processing

A Persian Q&A model based on the RoBERTa architecture, optimized for Persian Q&A tasks

BART-based extractive QA model trained on Squad 2.0 dataset with an F1 score of 87.4

A German question-answering model fine-tuned based on the GELECTRA Large architecture, excelling on German MLQA and XQUAD datasets