# Turkish text generation

Turkish-Gemma-9b-v0.1 is a Turkish text generation model developed based on Gemma-2-9b, optimized through continued pretraining, supervised fine-tuning (SFT), direct preference optimization (DPO), and model merging techniques.

A LoRA-adapted model based on google/gemma-2-9b, further pre-trained with Turkish Wikipedia data to enhance Turkish text processing capabilities

CosmosLLaMa-Instruction DPO is a large language model specifically designed for Turkish text generation tasks, capable of continuing text fragments in a coherent and contextually appropriate manner.

Turkish-Llama-8b-v0.1 is a fully fine-tuned Turkish text generation model based on LLaMA-3 8B, trained on a 30GB Turkish dataset.

A Turkish text generation model fully fine-tuned on 30GB of Turkish dataset based on LLaMA-3 8B

VBART is the first large-scale sequence-to-sequence language model pretrained from scratch on Turkish corpora, developed by VNGRS.

VBART is the first large-scale sequence-to-sequence language model pretrained from scratch on Turkish corpora, developed by VNGRS.

This is a Turkish GPT2 large model specifically designed for text generation tasks, capable of continuing given text fragments in a coherent and contextually appropriate manner.

Canary-750M is a pre-trained Turkish GPT-J 750M model, part of the Turkish Data Depository initiative.

A Turkish large language model based on the GPT-2 architecture, designed specifically for Turkish text generation tasks

A GPT-2 model trained on Turkish Wikipedia corpus, suitable for Turkish text generation tasks.

This is a Turkish text generation model fine-tuned based on the GPT2-Small architecture, specifically optimized for Turkish literary creation.

This is a fine-tuned version of the GPT2-Small English model, trained on Turkish Wikipedia articles, suitable for Turkish text generation tasks.