# Large-scale Language Model

A large-scale language model specialized for translation tasks developed by Preferred Networks, supporting English and Japanese mutual translation

This model is the GGUF version of rinna/nekomata-14b-instruction, compatible with llama.cpp for lightweight inference.

FLAN-T5 is an instruction-fine-tuned language model based on T5, achieving superior performance through fine-tuning on over 1,000 multilingual tasks with the same parameter count

ERNIE 3.0 is a large-scale knowledge-enhanced pre-trained model for Chinese language understanding and generation, developed by Baidu Research.

OPT is an open-source pre-trained Transformer language model developed by Meta AI, with parameter scales ranging from 125 million to 175 billion, designed to advance research in large-scale language models.

A large-scale Chinese pre-trained language model based on the Transformer architecture, trained on massive Chinese text.

XLM is a masked language model trained on English text, using BERT-style MLM objectives for pretraining, supporting English language processing tasks.

This is the Hugging Face transformers adaptation of the original dense 6.7B parameter model from the paper 'Efficient Large Scale Language Modeling with Mixtures of Experts' by Artetxe et al.

A converted version of the 2.7 billion parameter dense model based on the paper 'Efficient Large-scale Language Modeling with Mixture of Experts' by Artetxe et al.