# Multi-task Processing

Japanese large language model released by CyberAgent, distilled and optimized based on Qwen-32B

BioMistral-MedMNX is a specialized language model in the biomedical field created by fusing multiple pre-trained models. It uses the DARE and TIES fusion methods to optimize performance.

Wizard Lake 7B is a fusion model combining the next-generation WizardLM 2 7B model with a customized DolphinLake model, delivering outstanding performance.

LaMini-Flan-T5-248M is a 248M parameter model fine-tuned on the LaMini-instruction dataset based on google/flan-t5-base, belonging to the LaMini-LM series, specifically designed for responding to natural language instructions.

Medium-sized spaCy pipeline optimized for Turkish, including tokenization, part-of-speech tagging, morphological analysis, dependency parsing, and named entity recognition

CPU-optimized Korean processing pipeline with complete NLP functions including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.

Korean processing pipeline optimized for CPU, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.

Stanza is an efficient natural language processing toolkit for Dutch, providing functionalities from raw text processing to syntactic parsing and named entity recognition.

Large German language processing model provided by spaCy, supporting NLP tasks such as POS tagging, dependency parsing, and named entity recognition

A lightweight BERT model for self-supervised language representation learning in Persian