# Research Use

This model is converted from canopylabs/3b-zh-ft-research_release into GGUF format, suitable for Chinese text generation tasks.

This is a Chinese language model converted from canopylabs/3b-zh-ft-research_release to GGUF format, suitable for text generation tasks.

Pile-T5 Base is an encoder-decoder model trained on The Pile dataset using the T5x library, trained for 2 million steps with MLM objective, approximately 2 trillion tokens.

Yi-Ko-6B is an advanced version of the 01-ai/Yi model, further pre-trained with an extended vocabulary and Korean/English corpus, supporting bilingual text generation in Korean and English.

A version fine-tuned using the IFprompMKR dataset with qlora on the microsoft/phi-1_5 model, primarily for text generation tasks.

A vision-language model pre-trained on image-text pairs, based on Llama-2 70B architecture, suitable for image caption generation tasks.

LLaVA is an open-source multimodal chatbot, fine-tuned on GPT-generated multimodal instruction-following data based on LLaMA/Vicuna.

This series of repositories open-sources reproductions of Meta AI's LLaMA and LLaMA 2 large language models, but with significantly reduced model sizes. The llama1_s experimental version contains 1.8 billion parameters, while the llama2_xs experimental version has only 460 million parameters.

OPT is an open-source large language model series launched by Meta AI, with parameter scales ranging from 125 million to 175 billion, aimed at promoting open research in large-scale language models.