# Multitask Text Generation

An 8B-parameter large language model based on the Llama-3.1 architecture, offering multiple quantized versions in GGUF format

An 8B-parameter language model based on the Llama 3.1 architecture, created by merging multiple models with mergekit, capable of text generation

A 7B-parameter language model based on the Qwen2.5 architecture, created by fusing multiple pre-trained models using the TIES method

This is a 14B-parameter large language model merged using the SLERP method, combining two base models: li-14b-v0.4 and miscii-14b-0218.

Phi-4-Model-Stock-v2 is a large language model merged from multiple Phi-4 variant models using the model_stock merging method, demonstrating strong performance across multiple benchmarks.

A 1B-parameter quantized model based on Llama3.2 architecture, supporting text generation tasks with multiple quantization version options

A large language model developed by Japan's National Institute of Informatics, supporting Japanese and English, based on Transformer architecture with 13 billion parameters

A merged model based on multiple 8B-parameter Llama-3.1 models, optimized using the model_stock method

UNA-ThePitbull-21.4B-v2 is a large language model based on 21.4B parameters, with performance close to 70B models, integrating emotional intelligence and IQ, excelling in dialogue and text generation.

This is an 8B-parameter model based on the Llama-3 architecture, merged using the mergekit tool, with strong text generation capabilities.

NeuralStar_AlphaWriter_4x7b is a 7B-parameter language model built on Mixture of Experts (MoE) technology, specifically optimized for creative writing tasks by integrating four expert models specialized in different writing domains.

This is a 2B-parameter Portuguese large language model based on the Gemma architecture, specifically optimized for Brazilian Portuguese, supporting instruction-following and text generation tasks.

StrangeMerges_17-7B-dare_ties is the result of merging two models, Gille/StrangeMerges_16-7B-slerp and Gille/StrangeMerges_12-7B-slerp, using the dare_ties merging method via LazyMergekit.

Blurdus-7b-v0.1 is a hybrid model obtained by merging three 7B-parameter models using LazyMergekit, demonstrating excellent performance across multiple benchmarks.

Stealth-v1.3 is an open-source large language model developed by Jan, supporting offline operation on local devices to ensure user privacy.

supermario-slerp-v2 is a text generation model created by merging two 7B-parameter models using the SLERP method, demonstrating outstanding performance across multiple benchmarks.

supermario-v2 is a merged model based on Mistral-7B-v0.1, combining three different models using the DARE_TIES method, with strong text generation capabilities.

This model is created by merging OpenHermes-2.5-Mistral-7B and Intel's neural-chat-7b-v3-2 using the ties merging method, focusing on text generation tasks.

Misted-7B is a 7B-parameter large language model based on the fusion of OpenHermes-2-Mistral-7B and Mistral-7B-SlimOrca, primarily designed for text generation tasks.

This model is a merge of AIDC-ai-business/Luban-13B and Open-Orca/OpenOrca-Platypus2-13B, forming a 13-billion-parameter large language model based on the Llama 2 architecture.

MVP is a multitask supervised pretraining model based on the Transformer architecture, specifically designed for natural language generation tasks.