# Multi-task Text Generation

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

DeepSeek-R1-Distill-Llama-3B is a version obtained by distilling DeepSeek-R1 using the R1-Distill-SFT dataset based on the Llama-3.2-3B model, with text generation capabilities.

Gemma is Google's lightweight cutting-edge open model series, built with the same technology as Gemini, suitable for various text generation tasks.

This is a Mixture of Experts model obtained by merging multiple pre-trained language models using mergekit, aiming to create the most unconstrained text generation capability.

mera-mix-4x7B is a Mixture of Experts (MoE) model with half the scale of Mixtral-8x7B but comparable performance and faster inference speed.

RecurrentGemma is an open-source language model built on Google's novel recurrent architecture, offering more efficient long-sequence processing capabilities

Zephyr 7B Gemma is a language model fine-tuned based on google/gemma-7b, trained on publicly available synthetic datasets using Direct Preference Optimization (DPO), designed to serve as a helpful assistant.

BoreanGale-70B is a 70B-parameter large language model merged using a custom algorithm (NearSwap), combining the miqu-1-70b-sf and WinterGoddess-1.4x-70B-L2 models.

Marcoro14-7B-slerp is a fusion of two 7B parameter models using the mergekit tool, demonstrating outstanding performance on the Open LLM Leaderboard

TinyLlama is a 1.1B parameter Llama model pretrained on 3 trillion tokens, designed to provide compact and efficient text generation capabilities.

orca_mini_13b is a text generation model trained on multiple high-quality datasets, focusing on instruction following and dialogue tasks.

A Chinese-English sentiment analysis model fine-tuned based on Randeng-T5-784M-MultiTask-Chinese, supporting multiple sentiment analysis task output formats