# Multi-task processing

Kevin 32B is a large language model developed by Cognition AI, supporting an ultra-long context (40960 tokens) and focusing on CUDA kernel generation and reinforcement learning tasks.

Instella is a series of 3-billion-parameter open-source language models developed by AMD, trained on AMD Instinct™ MI300X GPUs, outperforming other fully open-source models of the same scale.

Llama3.1-Typhoon2-8B is a large Thai language model (instructional type) based on the Transformer architecture, capable of handling various language tasks and providing users with efficient and accurate language interaction services.

Tango-70B-Instruct is a large language model designed to enhance language performance in Spanish-speaking regions.

YiSM-34B-0rn is a large language model based on the fusion of Yi-1.5-34B and Yi-1.5-34B-Chat, designed to balance instruction-following capabilities with foundational model characteristics.

A language model optimized based on meta-llama/Meta-Llama-3.1-8B-Instruct, proficient in Spanish text generation

LaMini-T5-738M is an instruction-tuned model based on t5-large, fine-tuned on the LaMini-instruction dataset, with 738M parameters, and is one of the LaMini-LM series models.

LaMini-Flan-T5-783M is an instruction-following model fine-tuned on the LaMini-instruction dataset based on google/flan-t5-large, with 783M parameters, belonging to the LaMini-LM series.

Open-source Chinese conversational large language model optimized with instruction fine-tuning, specializing in Chinese cultural tasks, with 1.4B/2.6B parameters

This model is specifically designed for English texts and can simultaneously perform tasks such as punctuation restoration, capitalization correction, and sentence boundary detection.

CPU-optimized Korean processing pipeline with complete NLP capabilities including tokenization, POS tagging, dependency parsing, named entity recognition, etc.

Transformer pipeline (huBERT) for Hungarian HuSpaCy, containing multiple natural language processing components

Advanced pre-trained encoder-decoder model for Vietnamese based on Transformer architecture

BERT model pre-trained on UD_Russian for Russian POS tagging and dependency parsing

CPU-optimized Danish language processing pipeline including tokenization, POS tagging, dependency parsing, named entity recognition, and other complete NLP functionalities

A CPU-optimized Portuguese processing pipeline, including tokenization, POS tagging, dependency parsing, named entity recognition, and more.

CPU-optimized Polish natural language processing model supporting POS tagging, named entity recognition, dependency parsing and other tasks

Chinese version of T5-large model specialized in natural language conversion tasks